Energy-Balanced Task Allocation for Collaborative Processing in Wireless Sensor Networks

Yu, Yang; Prasanna, Viktor K.

doi:10.1023/b:mone.0000048550.31717.c5

Cited by 147 publications

(112 citation statements)

References 31 publications

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“…Finally, in [2], two approaches are presented for task assignment. The first is an optimal solution based on Integer Linear Programming (ILP), and the other is a polynomial time 3-phase heuristic approximation.…”

Section: Related Workmentioning

confidence: 99%

“…This accentuates the need for a task allocation mechanism that is both time and energy efficient. Similar to [2], we define task allocation as the assignment of tasks onto WSN nodes such that the following constraints are met: (a) a task is only paired with nodes matching its required roles and capabilities, and (b) a task can either be provided with the total capacity it requires or none at all -partial fulfillment is not allowed. The overall goal of the assignment changes according to the context.…”

Section: Introductionmentioning

confidence: 99%

“…This requires a dynamic task allocation mechanism, capable of reacting to contextual changes. Unlike the system model discussed in [2], the tasks we consider here could require the temporary assimilation of nodes with different capabilities to form teams. This allows us to perceive the problem of task allocation in a WSN as a k-way graph partitioning problem [3][4][5], where each node partition is assigned a task to serve.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Distributed dynamic context-aware task-based configuration of wireless sensor networks

ElGammal

Eltoweissy

2011

2011 IEEE Wireless Communications and Networking Conference

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Abstract-The complexity of handling multiple -often conflicting -tasks, coupled with the collaboration required by wireless sensor network (WSN) nodes to accomplish such tasks, exacerbate concerns about the effectiveness and longevity of the network. Handling multiple dynamic contexts and offering autonomic context-aware WSN management are severely limited by the network's resource constraints. This may affect the ability of sensors to join fully or partially in the missions of the network, restricting the quality of users' experience. Moreover, WSNs should work unattended and cannot assume global visibility or centralized services. Hence, we conceptualize next generation WSNs as autonomous distributed systems capable of dynamic and adaptive reconfiguration. Such networks should be capable of performing dynamic task allocation according to application demand, network conditions, and task context. In this paper we present an efficient distributed task allocation method for WSNs. We look at the task allocation problem in WSNs from a new perspective, where we show how it can be mapped to a clustering problem, and we leverage our previously proposed Affinity Propagation (AP) inspired clustering protocol [1] to solve it. We contrast our approach against both optimal and naïve greedy solutions. By means of simulation, we show that our method is capable of achieving near-optimal results at only a fraction of the optimal solution cost.

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Section: Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Distributed dynamic context-aware task-based configuration of wireless sensor networks

ElGammal

Eltoweissy

2011

2011 IEEE Wireless Communications and Networking Conference

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“…Localized task mapping and task scheduling have been jointly considered for real-time applications in mobile computing [7] and WSNs [8] recently. Task mapping and scheduling heuristics are presented in Reference [7] for heterogeneous mobile ad hoc grid environments.…”

Section: Related Workmentioning

confidence: 99%

“…Our proposed solution, Energy-constrained Task Mapping and Scheduling (EcoMapS), aims to map and schedule the tasks of an application with the minimum schedule length subject to energy consumption constraints. EcoMapS is based on the high-level application model that describes the task dependencies through Directed Acyclic Graphs (DAG) [8]. Therefore, EcoMapS can be used with arbitrary applications.…”

Section: Introductionmentioning

confidence: 99%

Cluster‐based information processing in wireless sensor networks: an energy‐aware approach

Tian

Ekici

Özgüner

2007

Wireless Communications

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SummaryEmerging Wireless Sensor Network (WSN) applications demand considerable computation capacity for in-network processing in resource limited WSN environments. To achieve the required processing capacity under energy consumption constraints, collaboration among sensors through parallel processing methods emerges as a promising solution. Although such methods have been extensively studied in wired networks of processors, its counterpart for WSNs remains largely unexplored. In this paper, a localized task mapping and scheduling solution for energyconstrained applications in WSNs, Energy-constrained Task Mapping and Scheduling (EcoMapS), is presented. EcoMapS guarantees energy consumption constraints while minimizing schedule length. EcoMapS incorporates channel modeling, concurrent task mapping, communication and computation scheduling, and sensor failure handling algorithms. Simulation results show significant performance improvements of EcoMapS over existing mechanisms in terms of minimizing schedule lengths subject to energy consumption constrains.

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QoS‐Based Communication Protocols in Wireless Sensor Networks

Vural

Tian

Ekici

2008

Algorithms and Protocols for Wireless Sensor Networks

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Energy-Balanced Task Allocation for Collaborative Processing in Wireless Sensor Networks

Cited by 147 publications

References 31 publications

Distributed dynamic context-aware task-based configuration of wireless sensor networks

Distributed dynamic context-aware task-based configuration of wireless sensor networks

Cluster‐based information processing in wireless sensor networks: an energy‐aware approach

QoS‐Based Communication Protocols in Wireless Sensor Networks

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