Self-Management Capacities in Future InternetWireless Systems

Vangelis Gazis, Apostolis Kousaridas, Costas Polychronopoulos, Tilemachos Raptis and Nancy AlonistiotiCommunication Networks Laboratory

Department of Informatics & TelecommunicationsUniversity of Athens

Panepistimioupolis, Ilisia 157 84Athens, Greece

e-mail: {gazis, akousar, cpoly, traptis, nancy}@di.uoa.gr

Abstract—Thanks to exponential growth rates, the Internethas doubled in size many times since its inception, nearlyfive decades ago. However, this tremendous growth hasbrought on an accumulating complexity in management tasks,thus undercutting the Internet’s manageability and provingdetrimental to further development. To address this predicament,the concept of a capacity for autonomic operation was proposedand later extended with artificial intelligence features to thusconverge on the vision of a self-managed Future Internet. Thecapacity for self-management builds on specific technologicalenablers, including a network monitoring infrastructure,mechanisms for decision making and decision appraisal aswell as advanced artificial intelligence features (e.g., machinelearning). This paper establishes the role of these capacities inrealizing a self-managed mode of operation for wireless Internetsystems. We present a case study where self-managementfeatures resulting from the combined application of deviceandnetwork monitoring and decision making are employed in asolution of a well-known planning and management problem inwireless networking.

Index Terms—Dynamic adaptation, next generation networks,autonomic operation, self-management, self-organization

I. I NTRODUCTION

The tremendous growth of the Internet stands as testimonyto the success its design principles but also as witness to theincreasingly complex task of managing the Internet infrastruc-ture in an efficient manner [1]. Nowadays, network manage-ment costs require a technically skilled human intellect and,therefore, constitute a major part of total cost of ownershipfor Internet systems.

Rising to the challenge, the vision of self-managing sys-tems has been adopted for Future Internet (FI) [2]. Un-der the umbrella self-management concept, self-awareness,self-configuration, self-protection, self-healing and self-optimization stand as prominent properties [3] of FI systems.The objective is to make the task of installing, configuring,op-erating and maintaining Internet infrastructures in an efficientmanner simpler and, thereby, easier and less costly.

In a wireless infrastructure, network management and, inparticular network planning, becomes a challenging task dueto the volatile and unpredictable nature of the wireless mediumand the mobility patterns of terminal devices. The increasing

footprint of WLAN technology in the information technologyand audiovisual equipment market segments suggests that alarge portion of FI devices will employ some form of wirelesstechnology. Due to the lack of coordination that characterizesapplications in the mass consumer market segments, staticand centralized solutions to wireless network planning proveinefficient in this chaotic environment [4].

The rest of the paper is organized as follows: Section IIsets the stage for the difficulty and complexity associated tonetwork planning for efficient resource allocations in a WLANsetting under distributed administration, and surveys relatedwork. Section III establishes design assumptions and derivesdesign requirements for a self-managed WLAN access pointto feed into Section IV introducing the respective architec-ture. Section V illustrates the application of the proposedaccess point architecture for common problems encounteredinwireless network management, in particular the optimizationof channel allocation among access points involving multipleparameters as part of the installation of a new access pointin a WLAN network. Finally, Section VI concludes the paperwith a brief discussion of the proposed approach.

II. PLANNING ISSUES IN WIRELESS NETWORKS

Due to the strong demand for good spectrum utilization,wireless network planning and management is a sophisticatedtask, which, more often than not, requires expert knowledge[5]. In a wireless infrastructure, the mobility of terminalde-vices and the volatile and unpredictable nature of the wirelessmedium render efficient planning a challenging task.

A. Problem statement

In cases where wireless networks of the same class (e.g.,IEEE 802.11a/b/g WLAN type systems) operating under dif-ferent administrations reside in the same geographical area(as defined by the bounds of radio signal transmission andreception), the problem of efficient radio resource allocationarises. Particularly for IEEE 802.11a/b/g systems whose foot-print is ever increasing in the home and enterprise marketsegments, efficient radio resource allocation in a dense urbanenvironment can be quite a challenge, due to the finite numberof interference-free channels available [6]. Channel allocation

in IEEE 802.11a/b/g systems may result in conflict wheremore than one adjacent (in terms of radio coverage) accesspoints use the same channel, thus causing a substantial dropin performance. In addition, as Fig. 1 illustrates, adjacentaccess points may use different channels but with a substan-tial nonetheless spectrum overlap [7], thus causing channelinterference and degrading performance. To further perplexsite planning, the hidden terminal problem involves situationswhere the transmission of interfering access points are beyondeach other’s reception range but within the reception rangeofclient devices, thus degrading system throughput (e.g., clientdevice A and access points AP1 and AP4 in Fig. 2).

Not surprisingly, a number of factors determine the effi-ciency of channel assignment in WLAN networks. Transmis-sion power levels and receiver sensitivity thresholds shapethe interference graph of network, thus determining channelinterference patterns. The spatial distribution of activemobileterminals and the temporal distribution of the their trafficload determines the nominal bandwidth share for each mobileterminal. Furthermore, individual traffic flows may requirespe-cific Quality of Service (QoS) levels, thus further complicatingthe achievement of efficient resource utilization.

B. Related work

The work in [8] proposes a new channel allocation mecha-nism for infrastructure-based IEEE 802.11 wireless networksin decentralized scenarios. The proposed mechanism operatesat the access point level to select the operating channel auto-matically based on station measurements exchanged throughthe IEEE 802.11k standard [7]. [9] evaluates the throughputperformance of different channel allocation strategies inanexperimental trial involving IEEE 802.11b systems. [10] pro-poses a set of algorithms to simultaneously solve the channelselection and user association problems in a fully distributedmanner. [11] proposes a simple decentralised algorithm forchannel allocation that is provably correct and requires nomessage passing or common administrative control betweeninterfering WLAN access points.

Leveraging the IEEE 802.11k capabilities, [8] uses compre-hensive state information regarding the wireless medium inde-cision making for channel assignment. While [11] establishesthe basic protocol for distributed WLAN channel selectionwithout communication in a stochastically converging manner,it does not address matters of optimum channel assignmentgiven specific criteria to consider (e.g., traffic load). Ourworkaddresses this setting by specifying an access point’s flowof activity that supports the exchange of detailed informationregarding the wireless resource so as to achieve an optimum

Fig. 1. IEEE 802.11b/g channel overlap at the 2.4 GHz band [7].

Fig. 2. Random topology IEEE 802.11b/g WLAN visualized according tothe unit disk graph model.

channel assignment pattern. To this end, we analyse and detailthe necessary state information at the access point level andillustrate signalling message exchanges for specific scenariosinvolving an autonomous self-managed mode of operation.

C. Theoretical background

Channel assignment in IEEE 802.11 WLAN systems isknown to be equivalent to the graph colouring problem [12], awell-known NP-hard problem in graph theory [13]. A simplegraph is an unweighted, undirected graph containing no graphloops or multiple edges [13]. A simple graphG = [V,E] isdefined as a set of verticesV = {v1, . . . , vN} and a set of(undirected) edgesE = {e1, . . . , eM : el = (u, v), 1 ≤ l ≤M,u 6= v, u, v ∈ V } connecting vertices with at most oneedge connecting any pair of vertices. Under these assumptions,graph colouring is concerned with determining the number ofcoloursψ required to assign a color to each vertexv ∈ V suchthat no two adjacent vertices are assigned the same colour. Agraph colouring using at mostk colours is called a (proper)k-colouring while the minimum number of colours requiredfor a proper colouring is called the graph chromatic numberχ(G) = min(ψ). Several algorithms based on contraction andsequential ordering have been developed to attack the graphcolouring problem, including Largest First (LF), Recursive-Largest-First (RLF), Backtracking Sequential Coloring (BSC)and Degree of Saturation (DSATUR) [14].

D. WLAN channel assignment

The WLAN channel assignment problem is isomorphicallymapped to the graph colouring problem as follows:

• The set of access pointsW = {w1, . . . , wN} is mappedto the set of verticesV .

• The pairs of access points{(w, z) : w, z ∈ W} withintransmission and reception range of each other is mappedto the set of edgesE.

• The set of available channelsC = {c1, c2, . . . , cD} ismapped to the set of available colours.

We note that, depending on whether cross-channel interfer-ence is assumed to be substantial or not, the set of availablechannels may or may not include channels with partiallyoverlapping spectrum bands. Herein we assume that cross-channel interference is a minor performance factor, therefore,all defined channels are mapped to the set of available colours.

III. D ESIGNING A SELF-MANAGED IEEE 802.11 WLAN

A. Design assumptions

Access points are assumed to be trustworthy and coop-erative, reporting actual (i.e., true) values in the messagesexchanged with peer access points and exhibiting the be-haviour specified in their negotiation and coordination protocol(e.g., protocol messages are not dropped intentionally). Forsimplicity of presentation and to preclude selfish behaviour, allaccess points are assumed to share the same objective functionfor purposes of channel assignment.

B. Design requirements

Self-management entails particular requirements in termsofthe set of situations where network systems are able to operatein a self-managing manner, namely:

1) Fully distributed control, i.e., being able to operate ina self-managing fashion without a central coordinatingentity.

2) Support for flexible decision making, i.e., being ableto make intelligent decisions regarding a device’s ownmode of operation by considering local and/or globalinformation (e.g., set of available channels).

3) Stability, i.e., ensuring that system operation convergesto or around a stable point of operation (e.g., one withoutan oscillatory pattern of channel allocation).

Taking into account the design assumptions and designrequirements described here, the next section presents thearchitecture and state chart of a self-managing access pointthat is able to select the optimal channel and consequentlyhandle the network capacity autonomously.

IV. A CCESS POINT ARCHITECTURE

A. State information

Each access point maintains the following state informationfor purposes of supporting a self-manageable channel assign-ment procedure that optimizes particular performance metrics.The latter are fully subsumed in and expressed through anobjective functionF embedded in each access point.k The number of known channels, henceforth termed

the channel reuse factor [5].c The currently allocated channel.Map The list of MAC addresses of its neighbouring (in

terms of radio transmission and reception) accesspoints.

cap The list of channels currently allocated to its neigh-bouring (in terms of radio transmission and recep-tion) access points.

Mwd The list of MAC addresses of the wireless devicescurrently associated to it (i.e., its client devices).

Mht The list of MAC addresses of access points meetingthe hidden terminal criteria with respect to thisparticular access point.

cht The list of channels of access points meeting thehidden terminal criteria with respect to this partic-ular access point.

KB A knowledge base where historical informationregarding c,Map, cap, Mwd, Mht and cht arerecorded on a periodical basis and exploited bylocal decision making processes seeking to optimizeperformance.

B. Local procedures

Each access point has the ability to develop its knowledgebase and the corresponding state information by exploitingthefollowing means: a) sensing the environment (Map, Cap), b)negotiating with neighbouring access points in order to retrieveMwd c) or even by interacting with a higher level networkmanagement element (e.g., network domain manager) if thelast is available. Albeit depicted in Fig. 3, the latter option isnot elaborated herein, due to space limitations.

C. Behaviour

Fig. 3. Activity Diagram for Access Point Channel Selectionor re-Allocation

Fig. 3 presents the activity diagram with the key stepsand interactions for channel selection or re-allocation after aninitial trigger. A channel (re-) selection process is triggered byone access point a) if it is bootstrapped b) or if the conditionsof the carrier and in general of the environment have changed

and the existing channel allocation should alter in order toserve the imminent capacity requirements. An increase in thenumber of mobile devices associated to an access points isa representative example that triggers a channel re-allocationprocess. Since this event increases the amount of data traffictransferred by the respective access points, a channel witha low interference level is necessary. Channel interference,due to transmissions on the same frequency and cross-channelinterference, due to transmissions on adjacent frequencies arethe elementary problems that each access point should solvetaking into account several criteria.

Each access point, after the trigger for channel selection orupdate has two options, either to select the optimal availablechannel or to launch a channel re-allocation process in therelative network area by updating also the channel relative-use pattern. The network area for an access point includesthe (one-hop) neighbouring access points and those (two-hop)access points that are not within each other‘s reception rangebut are within the reception range of mobile devices (i.e.,meet the hidden terminal situation). As depicted in Fig. 3, thecorresponding access point should initially retrieve the channelreuse pattern by the network area domain manager. If thereis not an associated domain manager, for an IEEE 802.11b/gWLAN, the channel reuse pattern is by default set to three (3),since there are three non-overlapping channels (i.e., channels1, 3 and 11) in the IEEE 802.11 standard [7].

Thereinafter, the access point discovers the neighbouringaccess points (e.g., [15]) and negotiates with them to retrievethe channel that they have been assigned and other parametersuseful for its decision making process (e.g., the number ofmobile devices that each access point serves).

After the negotiation phase with the neighbouring accesspoints, the node that has issued the channel selection or updateprocedure should identify whether there is an optimum (non-overlapping) channel in the corresponding network area toselect, according to the known reuse pattern. If there is nosuch channel (i.e., a non-overlapping channel) the access pointhas three options it can assess and select:

1) to select the optimal channel, partially overlapping dueto interference from adjacent channels. The optimalchannel from those that are not reserved in the corre-sponding geographical area is the channel which is lessinterfered according to the Fig. 1 allocation. Factors thatcome into play in the objective function involved in thiscase are:

• The number of mobile terminals associated to eachaccess point.

• The aggregate traffic of mobile terminals associatedto each access point.

2) To update the channel reuse pattern in the networkarea and then repeat the previous steps. Due to spacelimitations, this options is not detailed here.

3) To switch to a different channel assignment per accesspoint, without updating the channel reuse pattern. Thisaction is triggered in the case of a channel re-allocation

raised by an access point that has identified increasedcapacity requirements stemming from the associatedmobile terminals. The access points in the affectedgeographical (and network) area are thus reassigned aparticular channel. One of the policies that can be takeninto consideration for the assortment of the availablechannels is to assign channels with least interferenceto access points that serve more mobile terminals andconsequently, on average, require more channel capacity.

The logic of the procedure as it is depicted in Fig. 3 andit is briefly presented above is that if there is no availablechannel with zero interference by other channels, then the lessloaded/interfered channel should be selected, either througha re-allocation of channels assigned to access points in theassociated geographical area or not.

WLAN deployment is an incremental process in whichadditional access points are sequentially installed on site, pro-visioned with configuration state and, ultimately, bootstrappedin an operational network. Channel selection is an importantaspect of WLAN system provisioning that determines overallperformance. In the next section we detail the stages throughwhich self-managed access points goes through in selectingaWLAN channel and illustrate the signalling undertaken.

V. CASE STUDY: INSTALLING ADDITIONAL ACCESS POINTS

We assume a situation where an additional access point(AP4 in Fig. 4) has just been bootstrapped in an operationalWLAN network. As illustrated in Fig. 4, access point pairs(AP1, AP3) and (AP2, AP4) exhibit the hidden terminalcondition, while access point pairs (AP1, AP2) and (AP3,AP4) are directly within each other’s reception range and,thus, directly and autonomously aware of each other’s pres-ence on the wireless medium. In the initial condition, accesspoints AP1, AP2 and AP3 operate in an optimum channelassignment scheme, each occupying a unique WLAN channelwith no overlap to channels occupied by other access points.

Fig. 4. WLAN network topology right after bootstrap of an additional accesspoint.

Fig. 5. Message sequence chart for installation of an additional access point.

The emergence of access point AP4 kick starts the channelassignment procedure (Fig. 5) detailed subsequently.

1) AP4 after bootstrap initiates the channel selection pro-cess.

2) AP4 retrieves the list of available channels (e.g., chan-nels 1, 4, 6, 8, 11), taking into account a) the capabilitiesof the wireless standard supported by the AP (e.g., IEEE802.11g only), and, b) the policies rules that are definedby a national regulator or the network administrator.

3) AP4 scans the wireless carrier for the discovery ofbeacon frames [7] from neighbouring access points soas to find out which channels are used by neighbouringaccess points and their associated MAC addresses. ThusAP4 builts the list of the APs (AP3) that are directlyreachable since their transmission capacity is withintheir reception range.

4) AP4 identifies neighbouring APs that meet the hiddenterminal criteria by transmitting a broadcast request to

the mobile terminals (B) within its transmission range.The message contains the list of MAC addresses of theAPs discovered by it in the previous step. Thus, mobileterminals are informed on the neighbouring APs thatAP4 is able to detect autonomously. This informationwill reduce the number of reply messages, since onlythose terminals that are associated to an AP, which isnot included in the attached list, will be included in thereply from terminals.

5) Each mobile terminal that received the broadcast mes-sage scans the wireless medium for beacon frames indi-cating an AP and its associated MAC address. If an APwhose MAC is not included in the information conveyedby AP4 is detected, the respective MAC address andchannel in use are included in a reply message to AP4.The latter message contains the list of MAC addressesand channels in use for all APs (AP1, AP2) whichare not autonomously discovered by AP4 and whose

transmission range overlaps with the transmission rangeof AP4 in the location occupied by the particular mobileterminal.

6) The mobile terminal sends to AP4 the MAC address andchannel in use for the APs (AP1, AP2) it has detected.

7) AP4 builds the list of neighbouring APs taking intoaccount the listld = {AP3} of APs discovered duringthe sensing phase and the listli = {AP1, AP2} of APsinformed of by the mobile terminals. AP4 now has acomplete list of the APs that affect the performance of itschannel assignment decision, either directly or indirectly(e.g., due to the hidden terminal situation). ThereinafterAP4 consults its provisioned metrics in the calculationof the objective function so as to conclude to an optimalchannel assignment decision.

8) AP4 requests the mobile terminals that replied previ-ously to inquire each AP inli for the number of mobileterminals currently associated to it.

9) The respective mobile terminal inquires each AP inlifor the number of mobile terminals currently associatedto it.

10) AP2 responds to the mobile terminal with the totalnumber of associated mobile terminals.

11) The terminal conveys this information back to AP4 inits reply.

12) AP4 requests the total number of associated mobileterminals from neighbouring AP1.

13) AP1 responds to AP4 and sends the number of associatedmobile terminals.

14) AP4 inquires the neighbouring AP3 for the total numberof the associated mobile terminals.

15) AP3 responds to AP4 and sends the total number ofassociated mobile terminals.

16) AP4 having fully discovered it vicinity and the neces-sary performance parameters (e.g., number of mobileterminals associated to each AP) can now calculateinterference metrics for all involved out of the availablechannels.

17) AP4 selects the optimal channel (e.g., the one with theleast spectrum overlap).

18) AP4 switches to the selected channel.

VI. CONCLUSION

The increasing footprint of wireless technology in mass con-sumer market segments suggest that FI wireless networks willrequire properly designed self-management features to operateefficiently in this chaotic environment. Channel assignment is adeterminant factor of performance in WLAN installations thatrequires intelligence and coordination to achieve maximumpotential. To this end, we have specified and presented the be-haviour of a self-managing access point system that promotesefficient channel assignment schemes through the applicationof properly designed trade-off policies in a staged manner.Our approach aligns to the distributed and uncoordinatednature of independently administered WLAN networks whileallowing for a degree of centrality in decision-making and

system provisioning procedures through the engagement ofupdate procedures upon the provisioned channel reuse factor.Future extensions of our work involve the introduction ofmachine learning approaches in autonomous decision-makingfor purposes of WLAN channel allocation.

REFERENCES

[1] Gupta and Ankur, “Network management: Current trends andfuture perspectives,”Journal of Network and Systems Management,vol. 14, no. 4, pp. 483–491, December 2006. [Online]. Available:http://dx.doi.org/10.1007/s10922-006-9044-7

[2] A. Galis, H. Abramowicz, and M. Brunner, “Management andservice-aware networking architectures (mana) for futureinternets,”2009. [Online]. Available: http://www.fp7-moment.eu/

[3] SELFNET, “System deployment scenarios and uses cases for cognitivemanagement of future internet elements,” 2009. [Online]. Available:http://www.ict-selfnet.eu/

[4] A. Akella, G. Judd, S. Seshan, and P. Steenkiste, “Self-managementin chaotic wireless deployments,” inMobiCom ’05: Proceedings ofthe 11th annual international conference on Mobile computing andnetworking. New York, NY, USA: ACM Press, 2005, pp. 185–199.[Online]. Available: http://dx.doi.org/10.1145/1080829.1080849

[5] A. R. Mishra,Fundamentals of Cellular Network Planning and Optimi-sation: 2G/2.5G/3G... Evolution to 4G. John Wiley & Sons, 2004.

[6] A. Akella, G. Judd, S. Seshan, and P. Steenkiste, “Self-management inchaotic wireless deployments,” inMobiCom ’05: Proceedings of the 11thannual international conference on Mobile computing and networking.New York, NY, USA: ACM, 2005, pp. 185–199.

[7] IEEE, “Standard for information technology - telecommunications andinformation exchange between systems - local and metropolitan areanetworks - specific requirements - part 11: Wireless lan medium accesscontrol (mac) and physical layer (phy) specifications,” IEEE, Tech.Rep., 2007. [Online]. Available: http://standards.ieee.org/getieee802/download/802.11-2007.pdf

[8] M. da Silva and J. Ferreira de Rezende, “A dynamic channelallocationmechanism for ieee 802.11 networks,” Sept. 2006, pp. 225–230.

[9] J. Riihijarvi, M. Petrova, P. Mahonen, and J. Barbosa, “Performanceevaluation of automatic channel assignment mechanism for ieee 802.11based on graph colouring,” Sept. 2006, pp. 1–5.

[10] B. Kauffmann, F. Baccelli, A. Chaintreau, V. Mhatre, K.Papagiannaki,and C. Diot, “Measurement-based self organization of interfering 802.11wireless access networks,” May 2007, pp. 1451–1459.

[11] D. Malone, P. Clifford, D. Reid, and D. Leith, “Experimental implemen-tation of optimal wlan channel selection without communication,” April2007, pp. 316–319.

[12] J. Riihijarvi, M. Petrova, and P. Mahonen, “Frequency allocation forwlans using graph colouring techniques,” Jan. 2005, pp. 216–222.

[13] R. Diestel,Graph Theory, 3rd ed., ser. Graduate Texts in Mathematics.Springer-Verlag, 2005, vol. 173. [Online]. Available: http://www.math.uni-hamburg.de/home/diestel/books/graph.theory/

[14] W. Klotz, “Graph coloring algorithms,” Technical Uni-versity of Clausthal, Tech. Rep., 2002. [Online].Available: http://www.math.tuclausthal.de/Arbeitsgruppen/Diskrete/Optimierung/publications/2002/gca.pdf

[15] S. Thomson, T. Narten, and T. Jinmei, “IPv6 Stateless AddressAutoconfiguration,” Internet Engineering Task Force, RFC 4862, Sep.2007. [Online]. Available: http://www.rfc-editor.org/rfc/rfc4862.txt