Load Balancing in Wireless Sensor Networks using Kirchhoff's Voltage Law

Toumpis, Stavros; Gitzenis, Savvas

doi:10.1109/infcom.2009.5062084

Cited by 22 publications

(11 citation statements)

References 18 publications

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“…Theoretically, the congestion avoidance/control is directly proportional to the load balancing in the wireless networks [7]. One of the reasons for packet loss is congestion [8].…”

Section: Related Workmentioning

confidence: 99%

Reliability-constrained routing for traffic load balancing in Wireless Sensor Networks

Chughtai

Badruddin

Awang

et al. 2014

2014 5th International Conference on Intelligent and Advanced Systems (ICIAS)

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In recent years, a notable progress has been observed in the field of Wireless Sensor Networks (WSNs) due to their enormous number of applications. In this paper, a routing problem has been considered in a static WSN. Traditionally, routing mechanisms are based on a single objective optimisation function, e.g., the cost in terms of distance to find the shortest End-to-End (ETE) path from a source (S) to a destination (D). This behaviour may not be appropriate for long term reliable communication. We have considered a reliability-constrained multi-objective optimisation problem that implicitly captures the traffic load based on the Packet Delivery Ratio (PDR) along with the hop-count. The proposed technique selects an optimum ETE reliable path. The reliability is achieved by selecting the nodes with least congestion along the path from S to D that eventually balance the traffic load in the network. The result shows that the PDR and the hop count have a significant impact to select the best reliable ETE path.

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“…Theoretically, the congestion avoidance/control is directly proportional to the load balancing in the wireless networks [7]. One of the reasons for packet loss is congestion [8].…”

Section: Related Workmentioning

confidence: 99%

Reliability-constrained routing for traffic load balancing in Wireless Sensor Networks

Chughtai

Badruddin

Awang

et al. 2014

2014 5th International Conference on Intelligent and Advanced Systems (ICIAS)

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“…However, AODV and similar protocols have certain limitations [67], and new protocols providing better performance are the subject of constant investigation [71][72][73]. In order to provide a performance bound of the planning framework independent of the intricacies of specific routing protocols, a mechanism simulating optimal data routing is proposed.…”

Section: Optimized Routingmentioning

confidence: 99%

“…In order to split its flow out, it must reduce its transmission rate to the first node to award channel utilization resources to others. This is described through the total link utilization ratio constraint Eu < 1 [71] and incorporates the slack variable E to allow that agent to overload if needed. Finally Eq.…”

Section: Optimized Routingmentioning

confidence: 99%

Dynamic Mission Planning for Communication Control in Multiple Unmanned Aircraft Teams

et al. 2013

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A multi-UAV system relies on communications to operate. Failure to communicate remotely sensed mission data to the base may render the system ineffective, and the inability to exchange command and control messages can lead to system failures. This paper describes a unique method to control network communications through distributed task allocation to engage under-utilized UAVs to serve as communication relays and to ensure that the network supports mission tasks. This work builds upon a distributed algorithm previously developed by the authors, CBBA with Relays, which uses task assignment information, including task location and proposed execution time, to predict the network topology and plan support using relays. By explicitly coupling task assignment and relay creation processes, the team is able to optimize the use of agents to address the needs of dynamic complex missions. In this work, the algorithm is extended to explicitly consider realistic network communication dynamics, including path loss, stochastic fading, and information routing. Simulation and flight test results validate the proposed approach, demonstrating that the algorithm ensures both data-rate and interconnectivity bit-error-rate requirements during task execution.

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“…In [31], the Wireless Minimum Cost Problem is defined as a network optimization problem used for performing load balancing in wireless networks with a single type of traffic. The load balancing in this study is assumed to be the efficient distribution of the traffic so that the overall cost to the network is minimized.…”

Section: Congestion Management and Load Balancing Studies In Wsnsmentioning

confidence: 99%