Mobile agent itinerary planning for WSN data fusion: considering multiple sinks and heterogeneous networks

Abstract

Mobile agent (MA)-based middleware has been thoroughly investigated in the past few years as a means to address the efficiency, scalability, and reliability issues of data fusion applications on wireless sensor networks. Deriving an efficient itinerary for each MA to follow is of high importance, because itineraries determine to a large extent the overall performance of data fusion tasks. In this article, we present a novel algorithmic approach for efficient itinerary planning of MA objects undertaking data fusion tasks. We adopt a method based on iterated local search to construct the itineraries (ie, visiting sequences of source nodes) assigned to multiple traveling MAs. We apply alternative optimization criteria which aim either at minimizing the overall energy expenditure over all derived MA itineraries or prolonging the network lifetime. Furthermore, we propose algorithmic solutions for 2 realistic settings which have not been investigated in the past: firstly, the employment of multiple sinks that share the responsibility of MA-based data fusion tasks across the sensor field, and secondly, the consideration of heterogeneous sensor networks comprising nodes powerful enough to host the runtime environment required to execute MA code as well as "ordinary" nodes which lack these resources. Simulation tests verify the performance gain attained by our algorithmic methods against alternative itinerary planning approaches which involve multiple MAs.

Coleta oportunista de dados para a Internet das Coisas com o uso de otimização discreta

“…Os focos da proposta são uma distribuição mais uniforme do consumo de energia nos dispositivos e um roteamento autônomo do agente móvel para realizar a coleta e garantir o atendimento aos requisitos de serviço dos usuários. Gavalas et al propõem um mecanismo de itinerários estáticos para múltiplos agentes móveis e considera principalmente a eficiência no consumo de energia influenciada pelo aumento do tamanho do agente móvel a medida que o mesmo avança no itinerário [Gavalas et al 2017] e agrega informações dos nós do itinerário. Diferentemente da proposta apresentada neste artigo, ambos trabalhos não consideram que dados relevantes também podem ser coletados oportunisticamente nos dispositivos intermediários, enquanto o agente móvelé encaminhado, através do itinerário, de um nó fonte de dados para outro.…”

“…Muitas vezes, estes dispositivos contêm dados atualizados e relevantes que podem ser de interesse dos usuários da rede. O emprego de AMs vem sendo rediscutido como uma forma de maximizar a quantidade de dados coletados da rede [Gavalas et al 2017, Lu et al 2019.…”

Multi-mobile agent itinerary planning algorithms for data gathering in wireless sensor networks: A review paper

“…Most of the existing MIP algorithms have proposed a homogeneous network with one sink located at the center of the network. Of recent MIP, a heterogeneous network with multiple sinks has been proposed by Gavalas et al 34 In this article, the focus is on determining the optimal number of MAs in a homogeneous network topology with one sink. The existing algorithms reviewed include tree-based MIP, central location based MIP (CL-MIP), genetic algorithm based MIP (GA-MIP), directional angle based MIP, and greatest information in the greater memory based MIP (GIGM-MIP).…”

A Spawn Mobile Agent Itinerary Planning Approach for Energy-Efficient Data Gathering in Wireless Sensor Networks

“…This section presents a review of some of the existing MIP algorithms. It is noted that MIP algorithms can be classified into homogeneous networks with one sink [ 16 , 17 , 18 , 19 , 20 , 21 ], and heterogeneous networks with multiple sinks [ 22 ] (based on network topologies). The majority of the existing MIP algorithms are based on the homogeneous network.…”