Evolutionary multi-path routing for network lifetime and robustness in wireless sensor networks

Abstract

Wireless sensor networks frequently use multi-path routing schemes between nodes and a base station. Multi-path routing confers additional robustness against link failure, but in batterypowered networks it is desirable to choose paths which maximise the overall network lifetime -the time at which a battery is first exhausted. We introduce multi-objective evolutionary algorithms to find the routings which approximate the optimal trade-off between network lifetime and robustness. A novel measure of network robustness, the fragility, is introduced. We show that the distribution of traffic between paths in a given multi-path scheme that optimises lifetime or fragility may be found by solving the appropriate linear program. A multi-objective evolutionary algorithm is used to solve the combinatorial optimisation problem of choosing routings and traffic distributions that give the optimal trade-off between network lifetime and robustness. Efficiency is achieved by pruning the search space using k-shortest paths, braided and edge disjoint paths. The method is demonstrated on synthetic networks and a real network deployed at the Victoria & Albert Museum, London. For these networks, using only two paths per node, we locate routings with lifetimes within 3% of those obtained with unlimited paths per node. In addition, routings which halve the network fragility are located. We also show that the evolutionary multi-path routing can achieve significant improvement in performance over a braided multi-path scheme.

A Robust and Energy-Efficient Weighted Clustering Algorithm on Mobile Ad Hoc Sensor Networks †

“…Additionally, the algorithm is based on a flat structure and the routing overhead will be amplified. Besides many high complexity algorithms are presented to solve the problem of fault node with a flat structure instead of clustering [30][31][32], however, it also results in energy depletion of the sensors nodes. In [33], a full 2-connectivity restoration (F2CRA) algorithm and partial 3-connectivity restoration algorithm (P3CRA) algorithm for connectivity restoration are put forward.…”

“…Additionally, if it adopts a way of saving stable routing table, the great communication overhead will degrade the network performance. In order to solve this problem, some routing protocols are proposed, such as Directed Diffusion or Dynamic Sourcing Routing (DSR) [31,36]. The protocols are mainly to reduce communication overhead through increasing the computing cost since computing cost is relatively much less compared with communication overhead.…”

Two‐Layer Hierarchy Optimization Model for Communication Protocol in Railway Wireless Monitoring Networks

“…proposed a multiobjective evolutionary algorithm to optimize the routing chosen and traffic distribution issues that provided the optimal trade-off between the network lifetime and robustness [21]. Li et al investigated the energy optimization problem by joint frequency allocation, link scheduling, routing, and transmission power [22].…”

A Survey on Proactive, Active and Passive Fault Diagnosis Protocols for WSNs: Network Operation Perspective

“…These networks are normally application specific, such as, environmental surveillance [ 1 , 2 ], scientific observation [ 3 , 4 ], traffic monitoring [ 5 ]. Although ample research has been done on improving the reliability and robustness of these networks [ 6 , 7 , 8 , 9 , 10 , 11 ], network fault diagnosis has received little attention in the area of in situ network diagnosis for testing operational sensor networks under critical and crucial conditions. Fault diagnosis can help to extend the overall lifespan of WSNs, thereby enhancing the network’s ability to work for a longer period of time.…”