a threshold-based predictive scheme for mobile subscribers in publish/subscribe systems

A Threshold-Based Predictive Scheme for MobileSubscribers in Publish/Subscribe Systems

Fatma Abdennadher #1, Maher Ben Jemaa #2

# National School of Engineers of Sfax, University of Sfax, ReDCAD LaboratoryB.P.1173, 3038 Sfax, Tunisia

1 [email protected] [email protected]

1corresponding author

Abstract—In this paper, we present our strategy adopted todeal with the mobility into publish/subscribe. Specifically, wefocus on the management of the mobile users from one brokerto another. In fact, the topic of mobility into publish/subscribesystems may cause many problems such as the increasing of thetraffic into the network and the messages loss. To overcome theseproblems, we have created a selective scheme on the basis of anaccurate selection. In fact, a threshold value is devoted to bethe criterion for the selection of caching points. On the basis ofthis principe, we apply various network settings to explore theeffectiveness of our approach. Hence, we extract the improvementof our approach on the messages loss, the caching cost andthe propagation cost in function of buffer size, publication rate,period of disconnection and connect time.

Keywords-Distributed Networks; Mobile Computing; Publish/-Subscribe; Prediction Management; Performance Efficiency.

I. INTRODUCTION

Nowadays the propagation of the pervasive computing de-vices, with the emergence of network access technologies(mobile wireless, wireline, and Internet), has led all kinds ofdevices to access networks. So, all these facts has given rise tothe mobile computing paradigm. In this paradigm the users canbe assumed stationary while on-line, but change the physicalaccess points to the network. So, the users may temporarilydisconnect from the network. Then, upon their connection,they expect to recuperate the data disseminated while theirdisconnection occurs. This demands a flexible middlewareinfrastructure, based on a scalable interaction style, to copewith the dynamic nature of mobile computing. In this context,the publish/ subscribe model can be very promising.

The publish/subscribe paradigm shown in Fig. 1 consists ofa set of distributed nodes elaborating the communication intothe network. Two types of clients are existing based on theirroles which are subscribers and publishers. The subscribers areinformation consumers. The publishers are information pro-ducers. The messages are passed from publishers to interestedsubscribers through the brokers. The route from publishers toall interested subscribers is coordinated by brokers for assuringthe matching.

The potential of the publish/subscribe communicationmodel consists of the full decoupling of the interacted parties

in time, space, and flow [1], [2], [3]. This decoupling makesthe publish/subscribe systems flexible and scalable. Also, thebrokers remove all explicit dependencies between publishersand subscribers. In fact, the multicasting mechanism imple-mented by brokers decouples publishers from consumers.This makes the publish/subscribe system a good candidatefor mobile computing by inducing three important effects.The first effect is that a client can operate in the systemwithout being aware of the existence of other clients. So, theclient only know the structure of the event notifications forissuing its interest in the form of subscriptions. In practice,the publish/ subscribe approach could be easily exploited bya PDA to advertise its presence in a room and receive theservices published there. The second effect is the ability ofthe client to connect and disconnect without affecting theother components. The third effect is the suitability of thepublish/subscribe communication to cope with unannounceddisconnection of clients, which characterizes mobile networks.

Given the strength of this paradigm, a large number of pub-lish/subscribe middleware have been developed. These systemsdiffer along several dimensions. Two main dimensions areusually considered fundamental which are the expressivenessof the subscription language and the architecture of the eventdispatcher.

The expressiveness of the subscription language classifiesthe publish/subscribe systems into three categories which aretopic, type and content systems. The first two categories [4],[5], [6]are limited in the expressiveness. In the content-basedsystems [7], [8], [9], subscriptions contain expressions thatpermit sophisticated matching on the event content. In ourwork, we have applied our approach into a publish/subscribemiddleware providing a content-based subscription language.

Two types of architecture are proposed for publish/subscribesystems. In the centralized architecture a single component actas event dispatcher. So, the publish/subscribe system couldnot be scalable enough. Also, the risk of a single point offailure may occur. In the distributed architecture [10], [11],[12], a set of interconnected brokers coordinate in collectingsubscriptions coming from clients and in routing events. Thisarchitecture contributes to the reduction of network load and

International Journal of Computer Science and Information Security (IJCSIS), Vol. 14, No. 6, June 2016

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the increase of scalability. The topology of the distributedbrokers differs from system to system. Most existing publish/-subscribe systems are implemented for fixed environments. So,several extensions are needed to make these systems able tocope with mobile subscribers.

In recent years, more importance is accorded to the per-formance issues induced by the mobility of the users [13].To solve these issues we propose to predict the mobility ofsubscribers. This prediction is based on a dynamic selectionof the most probable locations that the subscriber moves toduring its run. Our approach aims at forwarding the requiredinformation for the mobile users at their new locations upontheir connection while minimizing the caching cost, the prop-agation cost and the messages losses.

Fig. 1. The publish/subscribe Model

The rest of the paper is formulated in this way: We givean overview of the management of subscriber mobility intopublish/subscribe systems in section II. Then, we presentthe principe of our approach and the strategy that we havefollowed in section III. After that, we explore the adequacyof our approach by applying various network settings andcompare it to the standard proactive scheme in section IV.Finally, section V concludes the paper.

II. RELATED WORK

The mobility is an issue examined in many fields [14],[15], [16], [17]. Precisely, in this section we give an overviewof studies which propose approaches for the management ofmobile subscribers into publish/subscribe systems. In fact, themobility of the subscribers is managed by three types ofapproaches. The first type is the durable subscriptions [18],[19], the second type is the reactive approaches [20], [21], [22],and the third type is the proactive approaches [23], [24], [25].Each type differs from the other by the time and the mannerthat the transmission of the cached publications is realized.

A. Durable Subscription Approaches

The approaches classified in the category of durable sub-scription are limited to the operation of disconnection andconnection to the same broker. As an example of approachesadopting this type of approach we find Elvin [19]. The

followed strategy is realized on the basis of proxies used forthe buffering of publications. Indeed, these proxies play therole of the disconnected subscriber in order to transmit to it thedesired interest upon its reconnection. Thereby, two roles areattributed to this proxy according to the state of the subscriberwhether it is connected or not. Hence, when the subscriber isdisconnected, the proxy is considered as a subscriber express-ing the interest of the disconnected subscriber. Consequently,when the subscriber reconnects, the proxy is transformed intoa server transmitting to it its cached publications.

The same category of strategy was adopted into JMS [18].In fact, we remark that this approach causes a considerableloss of messages when the subscriber does not reconnect tothe same broker. In addition, this induces a significant loadon the network by the fact of storing infinitely the interestof the disconnected subscriber into the old broker. In fact,the operation of caching is stopped only when the subscriberreconnects to the old broker. Hence, a serious degradation isinduced on the performance of the system.

B. Reactive Approaches for Mobile Subscriber

Many systems have deployed the reactive strategy to handlewith mobile subscribers. Rebeca [30], [31] is one of thosesystems. In fact, its strategy is elaborated on the basis of virtualcounterparts related to the old broker. The reconfigurationof subscriptions is accomplished as soon as the subscriberdetects the change of the broker. In fact, the junction brokerbetween the old and the new broker transmits the bufferedmessages. Hence, the junction broker is the only responsiblefor the handoff requests. So, a significant increase in thehandoff latency is induced. In addition, the junction brokerrisks to be overloaded by the massively quantity of messagesmoving through it. Therefore, the performance of the systemis affected.

The same type of strategy [21] was developed into SIENA[26], [27]. Indeed, this strategy is handled by the proxiesrelated to the brokers of the publish/subscribe system. Un-fortunately, the massive use of proxy components affects theperformance of the system. Also, many duplicated messagesare overloading the network and are not deleted due to theexpensive operation of elimination.

Reds [28] is another publish/subscribe system that imple-ments a reactive approach [22]. The basic idea of the adoptedstrategy was founded on the selection of each broker as acaching point for the publication as long as it has a subscriberin its subscription table interested on this publication. Thisapproach suffers from the overload on the client.

Another reactive approach [29] was presented into Jedi[20].The adopted approach runs as follows: The retransmissionof subscriptions is first of all elaborated by the new broker.This retransmission is required for tracing the new routes forthe publications. So, the publications matching the interestof the mobile subscriber are cached into the new broker.Consequently, the buffering is stopped in the side of the oldbroker. A major inconvenient in this approach is its limitedscalability.



Another reactive approach based on the event mediators wasproposed in [32]. The event mediators play the role of thebuffer for the publications of the mobile subscriber. Hence,the event mediator sends the stored publications to the mobilesubscriber upon its reconnection. The implementation of thisapproach is not clear and it suffers also from the limitedscalability.

In the same category of approaches, we find the strategyproposed in [33]. As the previous approaches, the old bro-ker buffers the publications for the mobile subscriber. As adrawback, this strategy suffers from the invocation of a highhandoff latency in the large network.

C. Proactive Approaches for Mobile Subscriber

The main objective of proactive approaches is the minimiza-tion of the transfer delay of the cached publications. Thereby,these approaches are most times used for streaming and real-time applications. As a result of this minimization of delay,an increase in the network load is induced.

As an example of proactive approaches, we find the strategyused in [25]. In fact, this approach is based on the exploitationof the neighbor graph. This latter represents the list of thebrokers that will may be visited by the mobile subscriber.Indeed, this graph is constructed upon the reconnection requestand the context transfer request invoked after the movementof the mobile subscriber. Thereby, all the brokers in the graphreceive the subscriptions of the mobile subscriber before itsmovement. As a consequence of applying this approach, thenetwork will be overloaded.

Another proactive approach was applied in [23], [24]. Thisstrategy employs a layer of replicators between publish/-subscribe system and clients. The replicators serve for thepositioning of virtual clients at the possible brokers that maybe visited by the mobile subscriber. A drawback of thisapproach is that the same subscription can be expressed bydifferent subscribers related to the same broker. So, this brokerrisks to cache similar publications. This is due to the fact thatthe caching is invoked per subscriber. The major inconvenientof this approach is the huge load on the network and theincapacity to cope with the failures or long time disconnectionof subscribers.

This section has demonstrated that the reviewed works haveaccomplished the support of mobility with distinct rates ofsuccess. In fact, the management of mobility in these worksposes different technological problems. Hence, these strategiesare not yet effective and efficient for the management ofmobility with no loss of messages. Also, they are characterizedby their limitation in the performance metric. The main goalof our approach is the management of mobility in a trans-parent manner by assuring high performance. As mentionedbefore, the architecture of the publish/subscribe system canbe distributed. In such cases, the management of mobilitymay affect the performance of the system due to the hightraffic. Hence, it is primordial to create a new strategy with areduced traffic. Also, our strategy requires to be flexible andscalable. To achieve such goals, our approach is based on the

analysis of the most probable brokers to be next visited bythe mobile subscriber. Next, we will perform an evaluation ofour approach to extract its gains comparatively to the standardproactive approach.

III. PROPOSED APPROACH

The attention for extending publish/subscribe systems tomobile applications was little. In fact, the most extensions werebased on a reactive strategy. This type of strategy suffers fromthe increase of network traffic and high handoff latency. Inour work, we tend to manage subscriber mobility efficiently.The main idea relies on the selective predictive caching ofmessages prior to the movement of the mobile subscriber bythe use of an intelligent mechanism.

Recently, the users in real scenarios of mobility are mov-ing according to repeated routines. Indeed, we can offera multitude of repeated movements every day for examplefrom home to office, from home to school, from home tomarket and vice versa. So, we can rely on the probability ofmovements between brokers to extract dynamic calculationsof probabilities on run time movement in order to offer anefficient management of mobility into publish/subscribe.

Our selective scheme follows a predictive strategy and hasproved its capacity to handle mobility with effectiveness. Thiseffectiveness is assured through a clever selection of a set ofbrokers serving for the caching of published messages duringthe disconnection of the mobile subscriber. This predictivestrategy in managing mobility contributes to the improvementof system availability. In fact, the past and actual states of themovement of the client are the key information for a correctprediction. Thereby, we use the information extracted fromthe actual movement of the subscriber in order to anticipatethe future movements. So, the different movements betweenbrokers are analyzed for the future prediction.

As we have said, our strategy is based on the probabilityof movements between brokers. Hence, two important valuesare calculated dynamically which are the handoff weights andthe threshold value. The handoff weight from broker A tobroker B is obtained by fractionating the total sum of handoffsfrom broker A to broker B by the total sum of handoffsfrom broker A to all the other brokers. Hence, the thresholdweight of broker A represents the average of weights from thisbroker. We obtain the weight threshold by fractionating thetotal sum of weights by the number of caching points. Hence,the selected caching points will require to have a handoffweight equal or greater than the threshold value. Thereby,a significant gain in the network traffic is approved by ourapproach through the elimination of the useless caching points.The following formulas clarify the two values with W is theweight, X is the number of handoffs, and nb is the numberof caching points.

WAB =XAB∑

N in caching points A

XAN

(1)



Wth(A) =

∑N in caching points A

WAN

nb(2)

The previous approaches do not consider any criterionfor the selection of caching points. Thereby, a considerabletraffic on the network is induced in large networks. Therefore,the criterion of weight becomes essential to eliminate theuseless caching points. So, the selected caching points arecharacterized by a weight value greater or equal than thethreshold value. Hence, the calculation of different weightsin a dynamic manner is recommended to obtain the updatedvalues.

In order to maintain the values updated, we apply uponeach movement a function named Update-Weight for thebroker from which the movement is invoked. In fact, foreach movement the new broker notifies the old broker aboutthe reassociation. So, the construction of caching points iselaborated correspondingly to the movements of the subscriberbetween brokers.

The storing operation in the caching points begins when themobile subscriber disconnects from its broker. To avoid a lossof messages into the caching points, the old broker is chargedto send to the set of caching points the buffered messagespublished until the operation of caching begins. Hence, whenthe new broker to which the mobile subscriber connects isamong the caching points, it will send directly the messagesto the mobile subscriber upon its reconnection.

The efficiency of the system is ameliorated since the cachingpoints with a low probability to be visited are eliminated.Indeed, the caching points are selected intelligently by com-paring accurately the weights values to the threshold value.Hence, the caching points subscribe in advance and store thepublished messages instead of the mobile subscriber duringits disconnection. A great major in our approach is its adapt-ability to all subscription language and to all general overlaystopologies.

The construction of the caching points is elaborated onthe basis of changes occurred into the network. According tothe movements of clients between the brokers, the values ofweights and threshold are updated. Thereby, the set of cachingpoints is dynamically varied. Indeed, the update of values isinvoked for each movement. Hence, new brokers are addedto the set of caching points and others are deleted. Therefore,we obtain a selection of caching points presenting the mostprobable brokers to be visited. Table I exhibits the selectivedynamic behavior of our approach. Thus, a considerable loadon the network is avoided. Added to that, we have tend toselect always the closest caching points from which the mobileclient recuperate its messages upon its reconnection when thenew broker is not among the caching points.

The quality of our approach can be measured by the factthat the new broker visited by the mobile subscriber belongsto the set of caching points. So, this indicates the exactitudein predicting the movement of the mobile subscriber. Hence,the recuperation of messages will be occurred directly from

this new broker. So, the exactitude value can be expressed bythe following equation:

Ex(t0,t) =number of handoffs to a caching point(t0, t)

number of handoffs(t0, t)(3)

This metric explores the adequacy of our approach insucceeding the prediction of the next accessed brokers. Hence,when the value of Ex(t0, t) is close to 1 that means that theselected caching points are useful enough for the prediction.

IV. EVALUATION

We achieved all our experiments on a prototype implemen-tation of a distributed publish/subscribe system (PADRES)[34]to which we extend our approach and the standard proactivescheme. For all the experiments the same mobility modelis applied. The evaluation of our approach is elaboratedaround the propagation cost, the caching cost and messageslosses.The results of these evaluations are elaborated accordingto the buffer size, the publication rate, and the period ofdisconnection. Through these different parameters, we extractthe gain of our approach compared to the standard proactivescheme.

A. Propagation cost

The propagation cost is the cost induced by the propagationof the subscriptions emitted by the mobile subscriber(ci) on theset of caching points. This propagation is occurred during thedisconnection of the mobile subscriber which can be definedby the following equations with nb caching points(Bi) is thenumber of the caching points of the old broker Bi fromwhich the mobile subscriber (ci) disconnected, and nb sub isthe number of subscriptions of the mobile subscriber emittedbefore its movement and not yet matched.

Propa cost(ci) = nb sub(ci) ∗ nb caching points(Bi) (4)

We have varied the frequency of movement from the highto the low as shown in Fig. 2. We have used 30 and 120seconds as average duration of connection. In the scenario ofhigh frequency of movement, the mobile subscriber connectsfor a short period of time, then it moves to other brokers.This results in triggering the propagation process in eachmovement. The number of propagated subscriptions dependson the subscription rate applied during the connection time.So, when the connection time is low, the number of propagatedsubscriptions is proportionally low. But, the high frequency ofmovement induces the increase of the propagation process. Incontrast, when we have a long connection time, we risk tohave an increased number of propagated subscriptions and areduced propagation process as the frequency of movementswill be reduced.



TABLE ISELECTIVE DYNAMIC CONSTRUCTION OF CACHING POINTS

Mobility Model B C B C B D B A B D B C B C BCaching points of A B B B B B BCaching points of B C C C C C C C C C,D C,D C,D C,D CCaching points of C B B B B B B B B B B B BCaching points of D B B B B B B B B

Fig. 2. Propagation cost

Fig. 3. Caching cost

B. Caching cost

The caching cost is induced by caching the publicationsduring the disconnection of the mobile subscriber (ci). Thiscost is calculated by the following formula with nb cachpub(ci) is the number of cached publications, Cach cost(ci)is the caching cost, nb caching points(Bi) is the number ofbrokers at which the caching is occurred for the broker Bifrom which the mobile subscriber disconnects.

The selection of the caching points by eliminating thosewith a weight value under the threshold value permits todecrease considerably the caching cost. We varied the periodof disconnection from 60 to 240 seconds. The increase in theperiod of disconnection induces an increase in the cachingcost. By reducing the period of disconnection and the publi-cation rate, the cachnig cost will be reduced.

Cach cost(ci) = nb rec pub(ci)∗nb caching points(Bi) (5)

Fig. 3 shows the impact of our approach in reducing thecaching cost on the network. The mobile subscriber movesbetween the brokers while varying the period of disconnectionfor different values of publication rates. The obtained resultshighlights the scalability of our approach and its capabilityto reduce the caching cost even for increased period ofdisconnection and publication rates.

C. Loss of messages

The loss of messages is a very important metric to considerin the evaluation of the performance. In our experimentations,we have used two values of buffer size 200 and 500, andwe have varied the publication rate for different period ofdisconnections. Fig. 4 shows that the loss of messages in-creases proportionally to the increase of the publication rate.In fact, as more the publication rate is important, as morethe number of stored messages will be important. Thereby,when the buffer becomes full, the cached messages will be



Fig. 4. Losses of messages for buffer size=200

Fig. 5. Losses of messages for buffer size=500

lost. So, as our approach presents a selected set of cachingpoints, the number of cached publications will be considerablyreduced. Consequently, our approach reduces significantly theloss of messages. This observation is confirmed by Fig. 5 whenthe publication rate is increased. So, for publication rate=27pub/min the loss of messages is minimized by 1350 messages.Thus, our approach permits to minimize notably the loss ofmessages especially for higher publication rate.

The performed tests examined how much our approach canreduce the loss of messages and the traffic of messages in adistributed environment under different values of publicationrates and period of disconnection. The obtained results showedthat a considerable reduce is assured by our approach forhigher publication rate. Hence, these tests have allowed usto compare exhaustively the behavior of our approach and thestandard proactive scheme under the same conditions.

V. CONCLUSION

In this paper, we evaluated our strategy for the managementof mobile subscribers into publish/subscribe networks. Variousnetwork settings are used to explore the adequacy of ourapproach compared to the standard proactive scheme. Theobtained results show how much our approach can reduceconsiderably the loss of messages, the caching cost and thepropagation cost in function of buffer size, publications rateand period of disconnection. In fact, our approach implementsan efficient service for mobile subscribers. The efficiency isrealized through a dynamic prediction for the next location ofthe mobile subscribers. The information for the prediction is

extracted dynamically from the past and actual states of themobile subscribers.

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a threshold-based predictive scheme for mobile subscribers in publish/subscribe systems

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