A Survey of Current Directions in Service Placement in Mobile Ad-hoc Networks

Wittenburg, Georg; Schiller, Jochen

doi:10.1109/percom.2008.43

Cited by 25 publications

(13 citation statements)

References 13 publications

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“…In fact, when reviewing current approaches to service placement in [110], we found that there are two distinct ways in which this area of research is generally approached:…”

Section: Overviewmentioning

confidence: 99%

Service Placement in Ad Hoc Networks

Wittenburg¹,

Schiller²

2012

SpringerBriefs in Computer Science

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Service provisioning in ad hoc networks is challenging given the difficulties of communicating over a wireless channel and the potential heterogeneity and mobility of the devices that form the network. In order to optimize the performance of the network over which a service host provides a service to client nodes, it is necessary to continuously adapt the logical network topology to both external (e.g., wireless connectivity, mobility, churn) and internal (e.g., communication patterns, service demand) factors. Recent proposals advocate that nodes should dynamically choose which nodes in the network are to provide application-level services to other nodes. Services in this context range from infrastructural services such as the Domain Name System (DNS) to user-oriented services such as the World Wide Web (WWW).Service placement is the process of selecting an optimal set of nodes to host the implementation of a service in light of a given service demand and network topology. The main questions addressed by service placement are: How many instances of the same service should be available in the network and cooperate to process clients' service requests; where these service instances should be placed, i.e., which nodes are best suited for hosting them;and when to adapt the current service configuration. The service instances of a distributively operating service are exact copies of the software component that provides the service, including both the executable binary and the application-level data. The set of nodes that host a service instance is referred to as the service configuration. A good service configuration increases the performance of a service according to application-specific quality metrics, while at the same time potentially reducing the overall network load. The key advantage of active service placement in ad hoc networks is that it allows for the service configuration to be adapted continuously at run time.In this work, we propose the SPi service placement framework as a novel approach to service placement in ad hoc networks. The SPi framework takes advantage of the interdependencies between service placement, service discovery and the routing of service requests to minimize signaling overhead. We also propose the Graph Cost / Single Instance (GCSI) and the Graph Cost / Multiple Instances (GCMI) placement algorithms. The SPi framework employs these algorithms to optimize the number and the location of service instances based on usage statistics and a partial network topology derived from routing information. The GCSI and GCMI placement algorithms only require minimal knowledge about the service they are tasked with placing in the network. They are novel in that they take the communication between service instances into account which is required to synchronize the global state of the service. Furthermore, when calculating the optimal timing of their placement decisions, the two algorithms explicitly consider the overhead of the actions required for implementing changes to the current service c...

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“…In fact, when reviewing current approaches to service placement in [110], we found that there are two distinct ways in which this area of research is generally approached:…”

Section: Overviewmentioning

confidence: 99%

Service Placement in Ad Hoc Networks

Wittenburg¹,

Schiller²

2012

SpringerBriefs in Computer Science

Self Cite

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“…Even in the case of undirected tree topologies, the complexity remains as high as O(kN ) [5] (N is the number of nodes in the network). In order to deal with the increased complexity, several near-optimal approaches have been proposed that can be categorized as either centralized or distributed [6]. The centralized approaches focus on greedy heuristics [7], [8], [9], [10], on linear programming [11], [12], [13], on primal-dual [14], [15], local search [16], [17], and other techniques [18], [19], [20], [21], [22], [23] that have been proposed in the past to deal with the increased complexity of the service placement problem.…”

Section: Related Workmentioning

confidence: 99%

“…Unique shortest path tree topologies (e.g., trees) are not uncommon; in fact, trees are formed frequently as a result of routing protocols in dynamic environments (e.g., mobile ad hoc networks [6]). In addition, the presence of a single service facility within certain network boundaries is also frequent.…”

Section: B Multiple Facilitiesmentioning

confidence: 99%

Scalable service migration in autonomic network environments

Οικονόμου

Stavrakakis

2010

IEEE J. Select. Areas Commun.

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Abstract-Service placement is a key problem in communication networks as it determines how efficiently the user service demands are supported. This problem has been traditionally approached through the formulation and resolution of large optimization problems requiring global knowledge and a continuous recalculation of the solution in case of network changes. Such approaches are not suitable for large-scale and dynamic network environments. In this paper, the problem of determining the optimal location of a service facility is revisited and addressed in a way that is both scalable and deals inherently with network dynamicity. In particular, service migration which enables service facilities to move between neighbor nodes towards more communication cost-effective positions, is based on local information. The migration policies proposed in this work are analytically shown to be capable of moving a service facility between neighbor nodes in a way that the cost of service provision is reduced and -under certain conditions -the service facility reaches the optimal (cost minimizing) location, and locks in there as long as the environment does not change; as network conditions change, the migration process is automatically resumed, thus, naturally responding to network dynamicity under certain conditions. The analytical findings of this work are also supported by simulation results that shed some additional light on the behavior and effectiveness of the proposed policies.

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“…The service placement problem is encountered in various networks such as transportation networks, supply networks and communication networks, [7], [13]. The globalization of the Internet and the proliferation of services and service demands have necessitated the careful selection of the location of the service.…”

Section: Introductionmentioning

confidence: 99%

“…That is, consider policies for moving the service position (one hop/node at a time) towards more effective positions based on local information, instead of requiring global information and solving continuously (in response to dynamic changes) a large optimization problem, [10], [8], [13], [14]. As it was shown for the migration policy introduced in [10], the service node needs to simply monitor the aggregate amount of data associated with the particular service that are exchanged through its neighbor nodes and decide on the service movement based exclusively on the information gathered through the (local) monitoring process.…”

Section: Introductionmentioning

confidence: 99%