opportunistic routing with admission control in wireless ad hoc networks
TRANSCRIPT
Computer Communications 55 (2015) 32–40
Contents lists available at ScienceDirect
Computer Communications
journal homepage: www.elsevier .com/ locate/comcom
Opportunistic routing with admission control in wireless ad hocnetworks
http://dx.doi.org/10.1016/j.comcom.2014.09.0070140-3664/� 2014 Elsevier B.V. All rights reserved.
⇑ Corresponding author.E-mail addresses: [email protected] (Y. Qin), [email protected] (L. Li),
[email protected] (X. Zhong), [email protected] (Y. Yang),[email protected] (Y. Ye).
Yang Qin a,⇑, Li Li a, Xiaoxiong Zhong a, Yuanyuan Yang b, Yibin Ye a
a Key Laboratory of Network Oriented Intelligent Computation, Shenzhen Graduate School, Harbin Institute of Technology, Shenzhen 518055, PR Chinab Department of Electrical and Computer Engineering, Stony Brook University, Stony Brook, NY 11794-2350, USA
a r t i c l e i n f o
Article history:Received 27 January 2014Received in revised form 24 June 2014Accepted 14 September 2014Available online 20 September 2014
Keywords:Opportunistic routingAdmission controlDifferent types of flows
a b s t r a c t
It is challenging to provide QoS in wireless ad hoc networks, one of the main problems that affects QoS inwireless ad hoc networks is the multi-hop nature of the network. In the traditional routing, if one node atthe optimal path is broken because of congestion or exhaustion of available energy, the whole path willbe broken, and the source must re-route again. Opportunistic routing (OR) is an efficient approach tosolve this problem, which can improve performance of system. However, it is difficult to provide betterQoS in OR due to the uncertainty of forwarding paths. In the meanwhile, existing OR protocols rarely con-sider providing service for different types of flows, and many of them cannot make a tradeoff betweenopportunistic path and limited resources of nodes. Therefore, in this paper, we present a novel Opportu-nistic Routing scheme which considers Admission Control of nodes for the different types of flows,namely ORAC. ORAC scheme first exploits a new flow admission control scheme which is based on band-width, backlog traffic and residual energy of nodes to select forwarding candidates. And then, ORAC usesa novel forwarding scheme to provide services for multiple different types of flows. In this way, ORACscheme can reduce the network congestion, and protect from any changes of traffic load for establishedroutes. Thus, it can provide better QoS for flows. Our extensive simulation results demonstrate that theproposed scheme ORAC can achieve better network performance compared to existing OR schemes interms of average delay, flow acceptance ratio and system throughput, routing overhead and energyconsumption.
� 2014 Elsevier B.V. All rights reserved.
1. Introduction
With the development of wireless ad hoc networks, to providebetter QoS for these types of networks is a meaningful and impor-tant issue. And this issue has been concerned by more and moreresearchers. Existing works on this topic have targeted toward sev-eral areas, such as QoS routing [1,2], QoS MAC [3], and QoS crosslayer design [4–6]. Despite the research efforts, there has beenno perfect solution in guaranteeing any form of hard QoS in wire-less ad hoc networks. Even formal QoS standards such as IEEE802.11e [7] (for MAC layer) have been criticized on its lack ofQoS support for multi-hop wireless networks. One of the reasonswhy QoS provisioning in wireless ad hoc networks is more chal-lenging as compared to centralized wireless networks is its
multi-hop nature. In multi-hop wireless ad hoc networks, packetscan be forwarded via intermediate nodes from the source to thedestination without centralized coordination. And many tradi-tional routing protocols fail to use the broadcast nature of wirelessnetworks and spatial diversity by choosing a fixed path as similarto wired links. When the current path is broken, the source willre-route again, and end-to-end QoS is difficult to guarantee.
Opportunistic routing (OR) [8] is an attempt to address theabove mentioned problem. OR exploits an elegant way to utilizethe broadcast nature of wireless links to achieve cooperative com-munication at the link layer and networks layer of static multi-hopwireless networks. Therefore, the network throughput can beimproved, and the transmission delay can be reduced by usingthe OR mechanism. Because OR has many characteristics, severalrepresentative works on OR have been proposed, such as [8–14].In [8], Biswas et al. first proposed the Extremely OpportunisticRouting (ExOR) [8], which integrates routing and MAC protocolto increase the throughput in multi-hop wireless networks. How-ever, ExOR’s forwarding paths can easily diverge, and the metricfor selecting candidate nodes only employs Expected Transmission
Y. Qin et al. / Computer Communications 55 (2015) 32–40 33
Count (ETX) [15]. These factors make it unclear how well ExORsupports multiple simultaneous flows.
Then, MAC-Independent Opportunistic Routing and Encoding(MORE) [9], Cumulative Coded ACKnowledgments (CCACK) [10]and the scheme in [11] combine OR and network coding [16] toincrease the end-to-end throughput. The characteristics of themare: MORE is an intra-session network coding scheme, CCACKadopts a cumulative coded acknowledgment scheme that allowsnodes to acknowledge network coded traffic to their upstreamnodes, and the scheme of [11] presents potential benefits of for-warding schemes that combine OR and NC, and gives a theoreticaloptimal scheme to provide a lower bound on the expected numberof transmissions, when traffic on a bidirectional unicast connectionbetween two nodes is relayed by multiple common neighbors.
Simple Opportunistic Adaptive Routing (SOAR) [12] adaptivelyselects forwarding nodes and uses priority-based timers to servicefor multiple simultaneous flows in wireless mesh networks. Coor-dinated Opportunistic Routing Protocol for Wireless Mesh Net-works (CORP-M) [13] uses a region based OR scheme to selectthe next forwarder, and the nodes in the region nearer to the des-tination with higher priority. In addition, Wang et al. proposed aCooperative Opportunistic Routing in Mobile Ad hoc Networks(CORMAN) [14], which extends the application environment ofOR from static multi-hop wireless networks to mobile ad hocnetworks.
However, these protocols do not consider how to provide a bet-ter QoS guarantee for different requirements under resource con-straints. In the meantime, in real networks, the bandwidth, thebuffer and the energy of nodes are limited in many cases. If wedo not consider these factors, it may result in network congestionand high packet loss, and then, QoS is unable to be guaranteed.
Of course, there are some routing schemes under networksresources constraints have been proposed. In [17], Ergin et al. pre-sented an admission control and routing mechanism for multi-ratewireless mesh networks, and their admission control scheme isbased on available bandwidth estimation. Moreover, Gao et al. [18]discussed the multi-rate any path routing scheme, which providesa bandwidth reservation for traffics. In addition, Zhao et al. [19] pro-posed Bandwidth-aware OR with considering Admission Controlnamed BOR/AC in mesh networks. In congestion control aspect,Naghshvar et al. [20] proposed an OR scheme with considering con-gestion diversity. In energy efficiency aspect, Mao et al. [21] pre-sented the energy efficient OR scheme. However, these protocolscan only consider single type of resource for the network nodes.
In summary, these existing works in OR do not consider differ-ent types of traffic flows, i.e., some traffics are audio or video, andothers are data, with different QoS requirements. And the real timerequirements (audio and video flows) should be given higherscheduling priority than the non-real time requirements (dataflows). Especially for the situation that the networks resources(energy, bandwidth and buffer) are limited, how to design a betteradmission control scheme for OR is a challenging but deservingresearch issue. For example, in military communication, thedevices of military can establish communication through wirelessad hoc networks. And these devices are installed the audio sensorand camera, which can collect the local audio and video informa-tion and send them to the other nodes through ad hoc networks,but these devices may have limited resources. Hence, to designan efficient routing scheme for this situation is important. Our pre-vious work [22] considers this problem in the Ad hoc On-demandDistance Vector routing (AODV) [23]. However, AODV is a tradi-tional routing protocol by choosing a fixed path, which does notefficiently utilize the broadcast nature of wireless networks. Tothe best of our knowledge, there is no related work on OR aboutQoS with admission control for different types of flows. This isthe motivations of our paper.
Therefore, we jointly consider the OR scheme and admissioncontrol, which is an efficient way to provide QoS in wireless adhoc networks. First, OR is a cooperative routing, which forwardeach packet to multiple one-hop neighbors by using the broadcastnature of wireless networks. When the current path is broken, orpart of messages does not successfully deliver to the destination,the potential neighbor forwarders which have received the mes-sages can cooperatively forward packets. Second, we exploit thenode’s admission control scheme before traffic admitting, whichtake the available bandwidth, the residual energy and backlog traf-fics of nodes into account. If a constructed route happens to involvesome congested nodes, the packets along this route may bedropped, in the meantime, affecting the existing flows passingthrough the congested nodes, resulting in more control packetsbeing created due to local route repair, etc. Therefore, the ideal caseis to minimize such situations as much as possible through properflow admission, and the likelihood of congested routes can bereduced through the implementation of the flow admission controlscheme, so as to provide a better QoS for flows.
In this paper, we propose a novel OR scheme joint with admis-sion control for different priority flows in wireless ad hoc net-works, named as ORAC (Opportunistic Routing with AdmissionControl). By considering the node’s available bandwidth, residualenergy and backlog in buffer before selecting the candidates, ORACis able to improve the network performance for different traffics.The contributions of our work can be concluded as follows.
(1) As far as we know, for different priority of traffics, ORAC isthe first opportunistic routing scheme, which comprehen-sively considers various kinds of node’s resources whenadmitting a new flow in wireless ad hoc networks. Theadvantage of ORAC is that it can guarantee QoS for differenttypes of flows, especially for multiple simultaneous flows.
(2) ORAC scheme contains two modules: First, a comprehensiveadmission control module is proposed, which is used todecide whether a coming data flow can be accepted or notfor some nodes during route discovery. Second, the novelcandidate selecting scheme and prioritization policy are pro-posed in opportunistic forwarding module. For differenttypes of flows, we can select different forwarding nodesand candidates list according to our forwarding scheme, soas to guarantee QoS for different requirements.
(3) We extensively evaluate the performance of ORAC. First, wepresent the average delay and cumulative percentage ofdelay with (ORAC)/without (ExOR) admission control. Thesimulation results show that ORAC can improve the perfor-mance compared with ExOR for multiple simultaneousflows. In addition, we compare ORAC with BOR/AC, in termsof flow acceptance ratio, system throughput, average delay,normalized routing overhead, and energy consumption ofnodes. The simulation results show that our ORAC schemecan achieve better performance than BOR/AC.
The rest of the paper is organized as follows. In Section 2, wepresent our flow admission control model in ORAC, which includesavailable bandwidth module, backlog traffic module and energyconsumption module. In Section 3, we propose our forwardingscheme in ORAC for different priorities of flows. In Section 4, weshow the simulation results. Section 5 gives the conclusion of ourpaper.
2. Flow admission control model in ORAC
In this section, we describe a new scheme joint flow admissioncontrol with OR. The purpose is to provide a proper method to
34 Y. Qin et al. / Computer Communications 55 (2015) 32–40
select forwarding candidates for a new incoming flow by usingflow admission control during the routing discovery. If a requestedflow arrives, we first compare its rate with the current availablebandwidth to decide whether the new flow can be admitted bythe node. Moreover, to provide better QoS and avoid longer queu-ing delay, the backlog packets in an intermediate node have alsobeen considered. If there are a large number of backlogs in a node’sbuffer, the new flow will be rejected by the node. In addition, thenodes must consume energy for receiving and forwarding packets,thus, the residual energy of nodes in multi-hop networks is also animportant factor that affects admitting of a new flow. If the abovethree criteria (available bandwidth, enough buffer space and residualenergy) are satisfied for a node, the node will participate in the routediscovery phase and will become a node of the forwarding candi-dates set. Note that, our scheme is based on 802.11e MAC protocols,which is contention-based. Therefore, we purely make use of esti-mated parameters in view that the network condition can bedynamic. In addition, assume there is a shared single channel forall the nodes. In the following three subsections we will providean explanation of the model from perspectives individually.
In our scheme, we consider a wireless ad hoc network, whosetopology is static, denoted by a directed graph G(V,E), where V isthe set of nodes and E is the set of virtual links in the wireless adhoc networks. Assume there are n nodes in the network, hence,V ¼ fn1;n2;n3; . . . ;ni;niþ1; . . . ;nng.
2.1. Available bandwidth
Assume that a typical node in a wireless ad hoc network has alimited bandwidth C to service incoming traffic flows. We denotean incoming packet of a particular flow with data rate qk
j , where jis the priority class of the flow and k is the number of the flow.There are m classes of flows in the network, the set of total classesdenotes {1, 2, . . ., j, . . ., m}. Assume class j has qj flows existing in anintermediate node ni, the flows set of class j can be expressed as{1, 2, ..., k, ..., qj} at node ni. When a new flow wants to access anintermediate forwarding node ni during the opportunistic routediscovery phase, it should satisfy the following condition.
qnewjþ1 þ
Xm
j¼1
Xqj
k¼1
qkj 6 C ð1Þ
where qnewjþ1 denotes the data rate of the new flow belonging to class
jþ 1,Pm
j¼1
Pqj
k¼1qkj denotes the total data rate of flows that have been
admitted by node ni from different priorities of classes. Eq. (1) consid-ers the bandwidth allocation for the flows based on the average rate.
2.2. Backlog traffic
In OR, we define a node as a congested node when its inflowsare more than it can cope. Thus, a node may be congested whenit has a low bandwidth (due to sharing of bandwidth with multipleneighbors or poor network condition, etc.) and its queue length islong (i.e., packets are not able to be transmitted fast enough). Forproviding better QoS, we also consider backlog traffics in the buf-fer. The second criterion aims to avoid congestion and to providebetter delay guarantee for a flow. Assume that at any time, anintermediate node ni contains
Pmj¼1
Pqj
k¼1wkj bits in total waiting
within its buffer, wkj is the number of bits waiting in a queue
belonging to a flow k of class j. For the intermediate node ni, whenit admits a new flow, it should satisfy the following inequality.
C �Xm
j¼1
Xqj
k¼1
wkj
Dj � Tkj
P 0 ð2Þ
where Dj is a soft delay bound parameter of class j in order to ensuremore weight given to higher priority traffic, Tk
j is the consumed time
that spends on transmitting the flow k of class j from source tointermediate node ni, which can be expressed.
Tkj ¼
Xni
x¼1
Tkj ðxÞ ð3Þ
where Tkj ðxÞ is the successfully transmission time of data flow from
node x to next hop xþ 1 for flow k of class j, which can beexpressed.
Tkj ðxÞ ¼
XL
l¼1
Tkj ðlÞ � pk
j ðlÞ ð4Þ
where l (1 6 l 6 L) is the number of retry, and L is the retry limitdefined in the IEEE 802.11 standard, pk
j ðlÞ is the successful probabil-ity of the lth attempt for flow k of class j, Tk
j ðlÞ is the time requiredfor the lth attempt of data flow k of class j transmission in node x,which can be expressed.
Tkj ðlÞ ¼ AIFSj þ Tbackoffj
ðlÞ þ Tkj�Data þ Rx � TACK þ Rx � SIFS ð5Þ
where SIFS is the short inter-frame spaces, AIFSj is the arbitrationinter-frame space defined in the IEEE 802.11e EDCA standard,Tbackoffj ðlÞ is the average back off time consumed in the lth attemptfor the flow of class j, Rx is the number of candidates of node x,Tk
j�Data is the time for transmitting data frame of data flow k withinclass j, and TACK is the time for transmitting ACK frame.
Note that, we assume that transmission attempts are indepen-dent from each other, and the successful probability for each classof traffic is different because of their different priority. Then, thesuccessful probability of the lth attempt for flow k of class j,denoted by pk
j ðlÞ, which can be calculated as
pkj ðlÞ ¼ ð1� dk
j Þl�1 � dk
j ð6Þ
where dkj is the success probability of each attempt for flows of class j.
2.3. Energy consumption
Wireless ad hoc networks are a special kind of wireless net-works, which allow a group of nodes to setup and maintain a tem-porary network by themselves, without the support of any fixedinfrastructure. In wireless ad hoc networks, the battery energy ofmany nodes is limited. Hence, we must consider the energy ofthese devices, estimating energy consumption of them in packetstransmission. We suppose that packet size is the same for differenttypes of flows, and the sending power of nodes is constant, thus,the energy consumption that spends on forwarding or receiving apacket is also the same for different types of flows.
The energy consumption of an intermediate node ni for success-ful transmitting one packet to its downstream node, denoted by EiC ,which is composed by three parts: the energy EiF is consumed toforward a packet, the energy EiR is consumed to receive a packet,and the energy EiAck is consumed to send an acknowledgmentpacket. In this energy module, the main energy consumption ofnodes is used to transmit packets, and some other factors, suchas energy attenuation of nodes, we do not consider them. Thus,we have
EiC ¼ EiF þ EiR þ EiAck ð7Þ
We suppose that EiT denotes the total energy of a node ni. More-over, according to the mechanism of OR, node ni should send anacknowledgment to its upstream node when it receives a packet.Hence, the residual energy Eir that the node ni forwards existingpackets belonging to the buffer queue of class j can be expressed.
Eir ¼ EiT �Xm
j¼1
Xqi
k¼1
wkj
pktsizeðEiF þ EiR þ EiACKÞ ð8Þ
Y. Qin et al. / Computer Communications 55 (2015) 32–40 35
where pktsize denotes the number of bits occupied by a packet size,Pm
j¼1
Pqik¼1
wkj
pktsize denotes the number of packets in the buffer queue of
class j for node ni. The formula (8) expresses the consumed energythat node ni spends to receive and forward existing packets in thebuffer.
Suppose that a new flow belonging to class jþ 1 contains rnewjþ1
packets, hence, the node ni can admit the new flow, it need tosatisfy the following inequality.
Eir � rnewjþ1 � ðEðjþ1ÞF þ Eðjþ1ÞR þ Eðjþ1ÞACKÞP 0 ð9Þ
where rnewjþ1 � ðEðjþ1ÞF þ Eðjþ1ÞR þ Eðjþ1ÞACKÞ denotes the consumed
energy that node ni spend to receive and forward a new flow of classjþ 1.
2.4. Flow admission control scheme
After introducing the available bandwidth, backlog traffic andenergy consumption model, we give our admission controlscheme. The key idea is that a node can admit a new flow if ithas sufficient bandwidth, energy, and buffer space. And then, wecan select it as forwarding nodes in the opportunistic route discov-ery phase. Hence, any intermediate node ni admits a new flow ofclass jþ 1 which contains rnew
jþ1 packets with data rate qnewjþ1 when
it satisfies the following inequality.
C �Xm
j¼1
Xqi
k¼1
qkj �
Xm
j¼1
Xqi
k¼1
wkj
Dj�Tkj� qnew
jþ1 P 0
Eir � rnewjþ1 � ðEðjþ1ÞF þ Eðjþ1ÞR þ Eðjþ1ÞACKÞP 0
8>><>>:
ð10Þ
The advantage of this scheme is that it is able to strike a balanceindirectly between admitting more flows and facing congestion,and provide better QoS for different requirements.
3. Forwarding scheme in ORAC
In this section, we introduce our forwarding scheme of ORAC fordifferent types of flows in detail. The ORAC scheme contains threecomponents: forwarding candidates set selection, candidates pri-oritization, and the opportunistic forwarding scheme. The formertwo parts determine the methods of selecting forwarding candi-dates and prioritization policies of forwarding candidates, andthe latter gives a forwarding scheme which contains to determinewhen a node updates its candidates list and how to provide differ-ent QoS for different types of flows. Next, we introduce themrespectively.
In the following, in order to express our ORAC scheme moreclearly, we exploit an example to introduce ORAC scheme. The net-work topology of the example is shown in Fig. 1, which contains 12intermediate nodes, a source and a destination. Assume there are 3classes of flows in the network, and the priority of class 1, class 2,and class 3 is in descending order.
3.1. Forwarding candidates set selection
How to select proper metrics for determining forwarding candi-dates set is very important. In ORAC protocol, we propose a newmethod for selecting the forwarding candidates set, which is basedon flow admission control described in Section 2. The details areexpressed as follows.
At the beginning of algorithms, the distance between any twonodes in the network should be calculated. This can be realizedeasily because the network topology is static. And for node ni inthe network, its one-hop neighbors can be determined when weset the transmission range of nodes. We select the nodes that thedistance between them and destination node is shorter than the
distance between ni and destination node within the one-hopneighbors, then, collect these nodes in a set, denoted by Si
ðSi ¼ fn1;n2; . . . ;nrgÞ. Moreover, we calculate the available band-width, backlog and residual energy of the nodes which are in setSi, and determine which nodes in set Si have sufficient resourcesto admit a new flow according to formula (10). After that, we storethe nodes that satisfy formula (10) in set Qi ¼ fn1;n2; . . . ;nwg(Qi # Si, w 6 r), where Q i is the forwarding candidates set of node ni.
As shown in Fig. 2, when a new flow of class 1 arrives, the nodeni (expect destination node) should first determine its availableneighbors set Si, e.g., SS ¼ fn1;n2;n3;n4;n5;n6g and S5 ¼ fn7;n8;n9gin Fig. 2. Then, to decide whether the nodes within Si can admitthe new flow of class 1 according to formula (10), and to constructnode ni forwarding candidates set Qi. Suppose that node n1 doesnot satisfy the condition of formula (10), thus, the forwarding can-didates set of node S is Q S ¼ fn2; n3;n4;n5;n6g. But the nodeswithin S5 all satisfy the condition of formula (10), so, the forward-ing candidates set of node n5 is Q5 ¼ fn7;n8;n9g. For the othernodes, they can also determine the forwarding candidates set ofthem using the similar method, such as the forwarding candidatesset of node n8 is Q 8 ¼ fn10;n11g as shown in Fig. 2.
After that, when another flow of class 3 arrives, as shown inFig. 3, the forwarding candidates set of nodes for the new flow willbe changed, because the network resources have been changed dueto some nodes have served for the flow of class 1 admittedrecently. As shown in Fig. 3, the candidates set of S within SS fornew flow of class 3 can be changed as QS ¼ fn1;n2;n3;n6g. Simi-larly, the other nodes will also change their forwarding candidatesset when the network resources changed, e.g., the forwardingcandidates set of node n6 is Q6 ¼ fn8;n9g, and the forwardingcandidates set of node n8 is Q 8 ¼ fn11g as shown in Fig. 3.
3.2. Candidates prioritization
After selecting the forwarding candidates set, we give a priori-tization policy to determine the priorities for these candidates. InORAC scheme, we use the priority metric @ i to decide the prioritiesof node ni when it admits a new flow with class j, which can bedefined as follows.
@i ¼ a�C �
Pmj¼1
Pqj
k¼1qkj �
Pmj¼1
Pqj
k¼1
wkj
Dj�Tkj� qnew
jþ1
C
þ b�Eir � rnew
jþ1 � ðEðjþ1ÞF þ Eðjþ1ÞR þ Eðjþ1ÞACKÞEiT
þ c�ðpif þ pirÞ
2þu� dSD � diD
dSDð11Þ
where pif is the forward delivery ratio of node ni, which indicatesprobability that a data packet successfully arrives at the recipient,pir is the reverse delivery ratio, which is the probability that theACK packet is successfully received by node ni, dSD is the distancefrom source to the destination node, diD is the distance from currentnode ni to the destination node, a;b; c and u are the weight factors,which can determine according to the requirements of application,such as, pay more attention to bandwidth, energy, link deliveryratio requirements or the distance to the destination, and satisfyingthe condition aþ bþ cþu ¼ 1.
When computing the node’s priority metric within the forward-ing candidates set according to formula (11), we can obtain a pri-ority queue by sorting the priority metric @ i in descending order,the larger priority metric @ i, the higher priority for forwardingpackets. And this priority queue is the candidate list.
As shown in Fig. 2, nodes in forwarding candidates set willcalculate their priority metric @i respectively, and return thesepriority metrics from downstream to upstream with probe packet.
2n
7n
3n
8n5n
6n
11n
4n
DS
9n
1n
10n
12n
Fig. 1. Network topology of an example.
2n
7n
3n
8n5n
6n
11n
4n
DS
9n
1n
10n
12n
2n
5n
3n
6n
8n
7n11n
4n
9n
10n
Candidates set of S
8Candidates set of n
5Candidates set of n
Sorted candidates list of S
5Sorted candidates list of n
8Sorted candidates list of n
high
low
priority
Fig. 2. The forwarding candidates set and candidates list for the flows of class 1.
36 Y. Qin et al. / Computer Communications 55 (2015) 32–40
For example, the node n5 in Fig. 2, it will receive the priority metric@7; @8 and @9. Node n5 sorts these priority metrics in descendingorder, obtains a candidates list n8;n7;n9 2 Q5 as shown in Fig. 2.For other nodes, the method of computing candidates list is similarto node n5. Hence, we can obtain forwarding priority of every for-warding candidate.
3.3. Opportunistic forwarding scheme
We summarize the opportunistic forwarding scheme ORAC inthis subsection. The node state and the packet format are similarto the classical OR protocol ExOR. Suppose that the data rate is var-iable, and all nodes are faithful, that is, the feedback messages aretrue.
At the beginning of the scheme, when a source wants to send aflow to the destination, it first sends a route probe packet whichcontains the messages of new flow for finding opportunistic path.Because the neighboring nodes and the distance between anytwo nodes can be determined in advance, thus, the available neigh-bors set Si of an arbitrary node ni in opportunistic path can also becalculated. After that, each node within available neighbors setdetermines whether it can admit the new flow according to
formula (10). And the nodes satisfying formula (10) will computetheir priority metrics @ i, then, piggyback them through route probepacket to their upstream nodes. Otherwise, they will keep silencein the route discovery phase. Hence, each node along the opportu-nistic path will keep a candidate list according to priority metric ofdownstream nodes. And in this process, we not only can find anopportunistic path but also obtain the forwarding candidates setand candidates list of each node in the opportunistic path.
Moreover, if one node ni contains different classes of flows withdifferent priorities, the higher priority of the flow has, the earlierthe flow will be transmitted. Because we select 802.11e MAC pro-tocol, which gives the different competition priority for differenttypes of flows, in the meantime, we also give different delay boundfor different classes of flows. For the flows within the same class,whose delay bound is the same, and the inter-frame space is thesame as well. In this situation, the order of sending packets forthese flows will be decided according to the opportunity that theflows access the channel. The earlier the flows access the channel,the earlier the flows will be transmitted.
The node ni copies the candidate list to each packet header andsends the data packets. The process of transmission is similar tothe ExOR scheme.
2n
7n
3n
8n5n
6n
11n
4n
DS
9n
1n
10n
12n
1n
6n
2n
3n
8n
9n11n
Candidates set of S
8Candidates set of n
6Candidates set of n
Sorted candidates list of S
8Sorted candidates list of n
priority
low
high
6Sorted candidates list of n
Fig. 3. The forwarding candidates set and candidates list for the flows of class 3.
Table 1Experimental parameters.
Parameter name Default values
The network area 1000 m * 1000 mTotal number of nodes From 20 to 60Link bandwidth 2 MbpsVBR 0–0.5 MpbsThe data packet size 1500 bytesSimulation time 950 sThe transmission range 250 mMax connection flow 20Energy consumed for sending a ACK packet 0.16e�3 euEnergy consumed for receiving a packet 1.8e�3 euEnergy consumed for forwarding a packet 3.6e�3 euThe initial energy of a node 300 euSlot time 9 lsSIFS 16 lsRetry limit (L) 7
Table 2802.11e MAC parameters for 3 classes.
Class Priority AIFSN CWmin CWmax
Class 1 2 2 3 7Class 2 1 2 7 15Class 3 0 3 15 1023
Y. Qin et al. / Computer Communications 55 (2015) 32–40 37
4. Simulation results
In this section, we evaluate the performance of our schemeORAC by running computer simulation using Network Simulatorns-2 (version 2.35). We compare ORAC scheme with the standardopportunistic routing protocol ExOR without flow admission con-trol for 3 classes of priority flows in terms of average delay andcumulative percentage of delay. In addition, we also compare ourscheme ORAC with BOR/AC in terms of system throughput, flowacceptance ratio, average delay, normalized routing overhead,energy consumption of nodes, and the network lifetime. The per-formance improvement and explanations of these results areexplained in the rest of this section.
In the simulation experiments, we set up a static wireless adhoc network with placed over a square of 1000 m * 1000 m. Thedata flows are generated with randomly selecting source and des-tination in this square area. The traffic in our simulation consists ofvariable-bit-rate (VBR) traffic using the UDP protocol, and therequired bandwidth of data flow is randomly selected from 0 to0.5 Mbps. Moreover, in the simulation, the ratio of weight factorsa : b : c : u is 0.2:0.2:0.3:0.3. In all simulation experiments, weuse IEEE 802.11e EDCA without RTS/CTS as the MAC-layer protocol,and ns-2 PHY settings exploit IEEE 802.11a. The detailed parame-ters of simulation scenarios are defined in Table 1. For energy con-sumption, our parameters are set in this paper referring to [24],and we convert them to our needed mode according to our param-eters (e.g., bandwidth and packet size). The energy usage is in arbi-trary energy units (eu).
For the simulation, we define three classes of flows, namely,class1, class2, and class 3, and their priorities and related parame-ters settings are shown in Table 2 (For different access categories(AC-j), AIFSj ¼ SIFSþ AIFSNj � aSlotTime, the value of Tbackoffj
ðlÞdepends on the minimum and the maximum contention window(CWmin and CWmax) of each class, these parameters are defaultsettings of 802.11e [7]). The delay bound parameters are arbitrarilydefined as 200 ms, 300 ms, and 500 ms for class 1, class 2, and class3 respectively, and the ratio of class 1:class 2:class 3 is 2:3:5.
4.1. Evaluation metrics
We exploit the following metrics to evaluate the performance ofthese routing schemes.
� Average delay (s): This metric is defined as the average length oftime to deliver data packets from source to destination success-fully, which can be calculated.
average delay ¼Pnumber of data packets received
i¼1 ti
number of data packets received
0.1
0.12
0.14
0.16
0.18
elay
(s)
Class 1 (ExOR)Class 2 (ExOR)Class 3 (ExOR)Class 1 (ORAC)Class 2 (ORAC)Class 3 (ORAC)
38 Y. Qin et al. / Computer Communications 55 (2015) 32–40
where ti is the time consumed for the packet i that have beensuccessfully received by destination node.� System throughput (Mpbs): This parameter reflects the effi-
ciency of the routing protocol. It is the amount of data packetstransmitted successfully from source node to destination nodein a given time period, which can be calculated.
1 2 3 4 50
0.02
0.04
0.06
0.08
No.of Simultaneous Flows
Ave
rage
D
Fig. 4. Average delay for each class of flows between ORAC and ExOR with
throughput¼number of data packets received�packet size�8ðtend� tstartÞ�1000�1000
where tend is the time that received the last packet, and tstart isthe time that sent the first packet.� Accept ratio: This parameter reflects the efficiency of the admis-
sion control scheme. It is the ratio between the number of datapackets for flows that have been received and the number ofdata packets for flows that have been sent, which can becalculated.
increasing the number of simultaneous flows.
0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4 0.45 0.50
10
20
30
40
50
60
70
80
90
100
Delay (s)
Cum
ulat
ive
Perc
enta
ge (%
)
Class 1 (ExOR)Class 2 (ExOR)Class 3 (ExOR)Class 1 (ORAC)Class 2 (ORAC)Class 3 (ORAC)
Fig. 5. Cumulative percentage of ExOR and ORAC schemes with increasing of delay.
accept ratio ¼ number of data packets receivednumber of data packets sent
� 100%
� Normalized routing overhead (load) [25]: The number ofrouting packets transmitted per data packet delivered atthe destination. Each hop-wise transmission of a routingpacket is counted as one transmission. It can be calculatedas follows.
normalized routing overhead
¼ number of routing packets sent and forwardednumber of data packets received by destination
� Average energy consumption: The total power consumptionof the battery operated nodes in the simulation, which canbe calculated.
average energy consumption
¼ the total power consumption of networknumber of nodes
� Network lifetime: Network lifetime is defined as the intervalbetween the beginning of a packet transmission of the net-work time until the first node failure due to batterydepletion.
Fig. 4 shows the average delay for each class of flows betweenExOR scheme and ORAC scheme for multiple simultaneous flowsfrom different source nodes under the scenario with 40 nodes.From Fig. 4, it can be seen that the average delay for all 3 classesof traffics with flow admission control (ORAC) is better than thatwithout flow admission control (ExOR). This is because ORACscheme selects proper nodes to forward packets according to theirresources, such as, available bandwidth, backlog traffics, and resid-ual energy of nodes, which can significantly increase the accep-tance ratio, and reduce transmission delay. In addition, fordifferent types of traffics, we set the order of forwarding packetsaccording to the priority of their classes, which can guaranteeQoS of different requests.
Fig. 5 shows the cumulative percentage of delay distribution forthe simulation scenario with 5 simultaneous flows. The resultsshow that the cumulative percentage of ORAC scheme is betterfor all classes of flows compared to ExOR scheme, which doesnot have flow admission control. We can observe that about 98%of packets of class 1 can be transmitted successfully within 0.1 s,and the packets can be delivered within the delay bound.
After comparing ORAC scheme with ExOR scheme. Because ourwork focuses on admission control in OR, In the following, we com-pare ORAC scheme with the bandwidth aware opportunistic rout-ing scheme BOR/AC, which is the first scheme consideringadmission control in OR, in terms of system throughput, average
delay, average flow acceptance ratio, normalized routing overhead,average energy consumption, and the network lifetime.
In Fig. 6, we compare ORAC scheme with BOR/AC scheme fromthe system throughput perspective. The results show that the sys-tem throughput of our scheme is largely improved as the numberof nodes increases. This is because we not only consider the avail-able bandwidth, but also consider the node’s buffer and energy fordata transmission. In addition, we also consider the link deliveryprobability and the distance with destination when determiningthe candidate list. Considering these factors comprehensively, wecan select more reasonable nodes to forward packets, which willreduce the congestion and packet loss of nodes, and utilize net-work resources more effectively. Hence, the system throughputof networks can be improved.
Fig. 7 shows the average delay of ORAC scheme and BOR/ACscheme with increasing the number of nodes. We can see thatour scheme ORAC has smaller delay than BOR/AC scheme. The rea-son is that our admission control scheme considers the delaybound of different types of flows, providing better QoS assurance.
In Fig. 8, we compare ORAC scheme with BOR/AC from the aver-age flow acceptance ratio perspective. The results show that theflow acceptance ratio of ORAC scheme is higher than BOR/AC asincreasing of number of nodes. This is because our admission con-trol scheme can select proper forwarding nodes according to theusage of current resources of nodes, which in turn reflects thecapability of nodes to deal with a new flow. Hence, the perfor-mance of average acceptance ratio has been improved in ORAC.
20 30 40 50 600
0.2
0.4
0.6
0.8
1
1.2
1.4
1.6
No. of Nodes
Syst
em T
hrou
ghpu
t (M
bps)
ORACBOR/AC
Fig. 6. System throughput of ORAC and BOR/AC with different number of nodes.
20 30 40 50 600
0.05
0.1
0.15
0.2
0.25
No.of Nodes
Ave
rage
Del
ay (s
)
ORACBOR/AC
Fig. 7. Average delay of ORAC and BOR/AC with different number of nodes.
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 160
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
Flows
Syst
em T
hrou
ghpu
t (M
bps)
ORACBOR/AC
Fig. 9. System throughput of ORAC and BOR/AC with a sequence of random flows.
Y. Qin et al. / Computer Communications 55 (2015) 32–40 39
Fig. 9 illustrates the system throughput of ORAC scheme andBOR/AC scheme with 20 flows coming in a fixed order in the sce-nario with 40 nodes. We can see that the performance of ORACscheme is better than BOR/AC, increasing the number of flows. Inaddition, for BOR/AC scheme, when flow 12 arrives, the remainderflows 13–20 will be rejected, thus, the system throughput keepsthe same value. But for ORAC scheme, when flow 14 is admitted,the remainder flow 15–20 will be rejected. The results show thatour scheme can server for more flows. The reason is that ouradmission control scheme properly selects forwarding candidatenodes according to several resources of nodes. And updates the for-warding candidate nodes when a new flow comes. Hence, resource
20 30 40 50 60
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
No. of Nodes
Acc
epta
nce
Rat
io
ORACBOR/AC
Fig. 8. Average flow acceptance ratio of ORAC and BOR/AC with different number ofnodes.
utilization of network nodes will be more fairness, and then moreflows can be admitted.
In Fig. 10, we present the normalized routing overhead of ourrouting scheme ORAC and the bandwidth-aware routing schemeBOR/AC, which all exploit OR to forward packets. We can see thatORAC scheme performs better than BOR/AC. The reason is thatORAC scheme narrows the size of forwarding candidates set ofthe node, eliminating the nodes that have no enough networkresources. Thus, the number of unsuccessful route request androute reply packets are reduced. As the number of the nodes inthe network increases, the number of the node’s candidatesincreases as well, inducing more overhead in these two schemes.
Fig. 11 illustrates the average energy consumption of each nodein the scenario that 20 VBR flows randomly select source and des-tination within 40 nodes at different time for two schemes ORACand BOR/AC. We can see that our scheme ORAC performs slightlybetter than BOR/AC. The reason is that there is a difference in can-didate selection criterion for these two schemes. BOR/AC only con-siders bandwidth to select paths while ORAC takes bandwidth andremaining energy into account. As the time increases, the networkload becomes heavy, and then the average energy consumptionbetween the two protocols also increases.
In Fig. 12, the network lifetime has been presented when we setthe initial energy of each node is 100eu. From Fig. 12, we can seethat ORAC performs better than BOR/AC. ORAC scheme tries tomaximize the network lifetime by fair utilization of nodes accord-ing to their energy. It can discover paths that consist of nodes withhigh energy level while it also avoids to use the nodes that alreadyhave participate enough times in packet transmission. As the num-ber of the relay nodes increased, the number of the possible pathsalso increases, leading to an increase in network lifetime.
20 30 40 50 600
1
2
3
4
5
6
7
8
No. of Nodes
Nor
mal
ized
Rou
ting
Ove
rhea
d ORACBOR/AC
Fig. 10. Normalized routing overhead of two schemes with different number ofnodes.
100 200 300 400 500 600 700 800 9000
20
40
60
80
100
120
140
160
Time (s)
Ave
rage
Ene
rgy
Con
sum
ptio
n (e
u)
ORACBOR/AC
Fig. 11. Average energy consumption of two schemes with time variance.
20 30 40 50 60280
300
320
340
360
380
400
420
440
No. of Nodes
Net
wor
k Li
fetim
e (s
)
ORACBOR/AC
Fig. 12. Network lifetime of two schemes with different number of nodes.
40 Y. Qin et al. / Computer Communications 55 (2015) 32–40
5. Conclusion
To provide better QoS in wireless ad hoc networks is a challeng-ing issue, and how to explore an efficient routing scheme to servicefor different priority flows is a difficult but meaningful work.
In this paper, we propose opportunistic routing scheme jointwith admission control named as ORAC for different priority flowsin wireless ad hoc networks. ORAC scheme mainly has two parts.One is the admission control scheme, which considers the availablebandwidth of current nodes, the capability of nodes that deal withpackets stored in nodes’ buffer within given time, and the availableenergy of nodes. In this scheme, we select proper forwarding can-didate nodes with enough resources to transmit data packets. Theother one is opportunistic forwarding scheme. In this part, we pro-pose a novel metric for selecting the forwarding candidates andsorting the priorities of candidates. In addition, our scheme canprovide better QoS for different types of multiple flows.
Further, our extensive simulation results show that the pro-posed scheme ORAC with admission control performs better thanthe standard OR protocol ExOR without admission control. AndORAC scheme can also improve the performance of systemthroughput, delay, acceptance ratio, overhead, energy consump-tion and lifetime compared to BOR/AC scheme.
Since the scheme ORAC is proposed for the case of static wire-less ad hoc network, how to cope with admission control foropportunistic routing in mobile ad hoc networks is part of ourfuture work.
Acknowledgements
This work was supported by the Science and Technology Funda-ment Research Fund of Shenzhen under grant JC200903120189A,JC201005260183A, ZYA201106070013A.
References
[1] S. Nelakuditi, Z. Zhang, R.P. Tsang, et al., Adaptive proportional routing: alocalized QoS routing approach, IEEE/ACM Trans. Network. 10 (2002) 790–804.
[2] Y. Xiao, H. Li, Local data control and admission control for QoS support inwireless ad hoc networks, IEEE Trans. Veh. Technol. 53 (2004) 1558–1572.
[3] X. Yang, N. Vaidya, Priority scheduling in wireless ad hoc networks, WirelessNetw. 12 (2006) 273–286.
[4] S. Toumpis, A.J. Goldsmith, Performance, optimization, and cross-layer designof media access protocols for wireless ad hoc networks, in: IEEE InternationalConference on Communications (ICC’03), Anchorage, Alaska, USA, 2003, pp.2234–2240.
[5] M. Conti, G. Maselli, G. Turi, et al., Cross-layering in mobile ad hoc networkdesign, IEEE Comput. 37 (2004) 48–51.
[6] Z. Ning, L. Guo, Y. Peng, et al., Joint scheduling and routing algorithm with loadbalancing in wireless mesh network, Comput. Electr. Eng. 38 (2012) 533–550.
[7] IEEE Std 802.11e-2005, Amendment8: Medium access control (MAC) quality ofservice enhancements, November 2005.
[8] S. Biswas, R. Morris, ExOR: Opportunistic multi-hop routing for wirelessnetworks, in: Proceedings of the 2005 Conference on Applications,Technologies, Architectures, and Protocols for Computer Communications(SIGCOMM’05), Philadelphia, PA, USA, 2005, pp. 133–144.
[9] S. Chachulski, M. Jennings, S. Katti et al., Trading structure for randomness inwireless opportunistic routing, in: Proceedings of the 2007 Conference onApplications, Technologies, Architectures, and Protocols for ComputerCommunications (SIGCOMM’07), Kyoto, Japan, 2007, pp. 169–180.
[10] D. Koutsonikolas, C. Wang, Y C. Hu, CCACK: Efficient network coding basedopportunistic routing through cumulative coded acknowledgments, in:Proceedings of 29th IEEE INFOCOM, San Diego, CA, USA, 2010, pp. 1–9.
[11] T. Mehmood, L. Libman, H.R. Dehkordi, et al., Optimal opportunistic routingand network coding for bidirectional wireless flows, Comput. Netw. 57 (2013)4030–4046.
[12] E. Rozner, J. Seshadri, Y.A. Mehta, et al., SOAR: Simple opportunistic adaptiverouting protocol for wireless mesh networks, IEEE Trans. Mob. Comput. 8(2009) 1622–1635.
[13] M.M. Ajmal, S.A. Madani, T. Maqsood, et al., Coordinated opportunistic routingprotocol for wireless mesh networks, Comput. Electr. Eng. 39 (2013) 2442–2453.
[14] Z. Wang, Y. Chen, C. Li, CORMAN: a novel cooperative opportunistic routingscheme in mobile ad hoc networks, IEEE J. Sel. Areas Commun. 30 (2012) 289–296.
[15] D.S.J. De Couto, D. Aguayo, J. Bicket et al., A high-throughput path metric formulti-hop wireless routing, in: Proceedings of the 9th Annual InternationalConference on Mobile Computing and Networking (MobiCom’03), San Diego,CA, USA, 2003, pp. 134–146.
[16] R. Ahlswede, N. Cai, S.Y.R. Li, et al., Network information flow, IEEE Trans.Inform. Theory 46 (2000) 1204–1216.
[17] M.A. Ergin, M. Gruteser, L. Luo, et al., Available bandwidth estimation andadmission control for QoS routing in wireless mesh networks, ElsevierComput. Commun. 31 (2008) 1301–1317.
[18] X. Gao, F. Wu, X.F. Gao et al., BREW: A bandwidth reservation protocol formultirate anypath routing in wireless mesh networks, in: Proceedings of IEEEWireless Communications and Networking Conference (WCNC’13), Shanghai,China, 2013 pp. 1327–1332.
[19] P. Zhao, X. Yang, J. Wang et al., BOR/AC: bandwidth-aware opportunisticrouting with admission control in wireless mesh networks, in: Proceedings of31st IEEE INFOCOM, Orlando, FL, USA, 2012, pp. 2701–2705.
[20] M. Naghshvar, T. Javidi, Opportunistic routing with congestion diversity inwireless multi-hop networks, in: Proceedings of 29th IEEE INFOCOM, 2010,San Diego, CA, USA, pp. 1–5.
[21] X. Mao, S. Tang, X. Xu, et al., Energy efficient opportunistic routing in wirelessnetworks, IEEE Trans. Parallel Distrib. Syst. 22 (2011) 1934–1942.
[22] Y. Qin, Y. Yang, C.L. Gwee et al., A flow admission control scheme for QoS inwireless ad hoc networks, in: Proceedings of IEEE Global CommunicationsConference (GLOBECOM’12), Anaheim, CA, USA, 2012, pp. 5734–5739.
[23] C.E. Perkins, E.M. Royer, Ad-hoc on-demand distance vector routing, in:Proceedings of the Second IEEE Workshop on Mobile Computer Systems andApplications (WMCSA’99), New Orleans, LA, USA, 1999, pp. 99–100.
[24] Y. Qin, Y.Y. Wen, H.Y. Ang et al., A routing protocol with energy and trafficbalance awareness in wireless ad hoc networks, in: Proceedings of 6th IEEEInternational Conference on Information, Communications and SignalProcessing (ICICS’07), 2007, Singapore, pp. 1–5.
[25] C.E. Perkins, E.M. Royer, S.R. Das, et al., Performance comparison of two on-demand routing protocols for ad hoc networks, IEEE Pers. Commun. 8 (2001)16–28.