Elsevier

Ad Hoc Networks

Volume 64, September 2017, Pages 53-64
Ad Hoc Networks

Review article
A distributed multi-path routing algorithm to balance energy consumption in wireless sensor networks

https://doi.org/10.1016/j.adhoc.2017.06.006Get rights and content

Abstract

A large use of applications of Wireless Sensor Networks (WSNs) pushes researchers to design and improve protocols and algorithms against the encountered challenges. One of the main goals is data gathering and routing to the base station (through the sink nodes) with lack of acknowledgement and where each node has no information about the network. Unbalanced energy consumption during the data routing process is an inherent problem in WSNs due to the limited energy capacity of the sensor nodes. In fact, WSNs require load balancing algorithms that make judicious use of the limited energy resource to route the gathered data to the sink node. In this paper, we propose a balanced multi-path routing algorithm by focusing on the residual energy and the hop count of each node to discover the best routes and to insert them into the routing table. The main idea of this algorithm comes from Ant Colony Optimization (ACO) and automata network modelization. Hence, the potential performance of the proposed algorithm relies on the best route to be selected which should have the minimum number of hops, the maximum energy and weighted energy between participating nodes to extend the lifetime of the network.

Introduction

Wireless Sensor Networks (WSNs) have attracted a great number of researchers during the last decades. The relevance of this area is strongly related to the explosion of new mobile devices and wireless sensors, which provide many important functions like self-monitoring environments without human beings’ intervention and energy suppliers [1], [2], [3]. Recent technological advances [4] have enabled the development of small-size (a few cubic centimetres), low-cost, low-power, multi-functional sensor devices. A WSN consists of a large number of sensor nodes with limited resource: battery power, capacity of computation, memory and radio range. These autonomous devices are used in a variety of contexts: geophysical monitoring, precision agriculture, habitat monitoring, transportation, chemical composition, seismic activity, acoustic properties, load pressure and so on. The main goal of WSNs is to sense periodically events from some interesting area and to route them as digital data to the base station. Many challenges are encountered before forwarding data to the base station such as data gathering, coding, aggregation, encryption and routing. Moreover, WSNs have to cope with a limitation of these resources. Routing data among nodes with aware energy consumption is one of the primary issues encountered when using this kind of network. Before discussing our contribution, it seems desirable to recall three main challenges in the design of an efficient routing algorithm for a WSN.

In large-scale WSNs the energy balancing consumption is an inherent problem in many-to-one traffic patterns. According to [5], scalability is the essential property for the successful performance of any network involving a large number of nodes, as is the case of wireless sensor networks consisting of large numbers of cooperating low-powered nodes capable of limited computation, wireless communication, and sensing. A scalable network [6] is a network which grows with increasing network load. Protocols must thus scale well with the number of nodes. This may often be achieved by using distributed algorithms, in which sensor nodes only communicate with nodes in their neighbourhood, whereas centralized approaches are not applicable, especially because of the single point of failure problem.

Ad-hoc routing algorithms focus on avoiding congestion issues or on maintaining connectivity when faced with mobility of nodes, they do not consider the limited energy supply of nodes. For wireless sensor networks, however, with a large number of energy constrained sensors, it is very important to design a fast algorithm allowing the sensors to minimise the energy used to communicate information from the nodes to the processing center. The problem with many routing algorithms is that they minimize the total energy consumption in the network by concentrating on improved methods to reduce energy consumption on network nodes. In this paper, the proposed method seeks to investigate the problem of balancing energy consumption by exploiting the nodes which have enough residual energy.

Sensors are sensible to failure due to their small size and limited on-board energy supply, in particular when they are deployed in a harsh environment. For a single node the failure may be caused by battery depletion, malfunction due to external hazard, or it may come from simultaneous failure of a multiple set of nodes. In our proposition, we have a multiple entrance in the routing table for each target to ensure energy aware expending and fault tolerance by selecting the second target in case of losing a node on the best routes.

In this paper, we will design and implement a distributed routing algorithm to work on balancing energy in WSNs. As a main contribution of our paper, we show that the lifetime maximization is ensured by efficiently avoiding the nodes which have low residual energy. To reach this goal, we have exploited Ant Colony Optimization (ACO) by flooding the network from the sink node in order to discover adequate paths. During network flooding, any node computes an energy factor value Fi, for each received route request, before inserting it into its routing table. Indeed, the value of Fi plays an important role for selecting the convenient route. Hereafter, each network node selects the best route by focusing on the inserted values of Fi. On the other hand, a hop count parameter is also introduced in the proposed algorithm. As shown in Table 1, the values are ordered by hops and for each cloud (set of routes that have the same hop number) the values are ordered by the energy factor priority (hop count and Fi are considered as pheromone). Indeed, this principle is useful to select the best route among a set of shortest paths. In case that the best route is unable to route data (the energy mean is below the threshold), the concerned node starts exploring other routes or the next cloud, to satisfy an energy factor threshold Fth.

The remainder of this paper is organised as follows: Section 2 describes some work for energy balancing in WSNs, where we have also highlighted the analysis of used resources and energy for each of the described techniques in order to deduce their advantages. Suitable ways to formulate the problem are presented in Section 3, which is followed in Section 4 by a discussion of the main extracted results. Finally, a conclusion and a discussion are presented in Section 5.

Section snippets

Related work

Much work has been proposed on multi-path routing protocols, but balancing energy within sensor networks is a big challenge for researchers. A flooding network technique to discover routes between nodes is implemented in many proposed routing schemes for WSNs. In [7], the authors use a flooding technique to find a shortest route but it is not always useful for energy consumption where detected routes have no sufficient energy to send data between a source and the destination. Otherwise, we

The proposed energy balancing algorithm

What we describe here is our contribution to define multiple routes between a given node ni and the source node (eventually the sink node) by selecting a subset of all existing routes. The defined technique is inspired from an ant colony optimization algorithm to classify the discovered routes by priority. To reach this end, we assume that a colony of ants discuss how to discover the best paths between the colony and the food, where the food is dispersed in random points. Every point has been

Simulation and results

This section evaluates the effectiveness of the energy factor Fi and of the n-Cloud for energy balancing in WSNs using the algorithmic techniques introduced in the previous section. Moreover, the proposed algorithm is compared with shortest path and equiproportional algorithms in order to show its efficiency. We aim to validate the proposed distributed routing algorithm in which we have considered the energy of sensors as a critical resource. To reach this end, an experimentation has been done

Conclusion

In this work, an energy factor routing algorithm was proposed to balance the energy consumption at the levels of each sensor and of the whole network. Altogether, we can notice that the proposed model takes into account the resource restrictions and the lack of initial knowledge, by starting with the identifier of each node and using the model [20] to evaluate the residual energy. The efficiency of this algorithm for path discovery and selection was inspired from ant colony optimization. Any

Acknowledgement

This paper has been written while the first author was visiting the Wireless Sensor group at Lab-STICC in Brest, France. Financial support through the PNE program established by the government of Algeria is gratefully acknowledged.

Abdelkader Laouid received the MSc. degree in computer science from the University of Bejaia, Algeria, in 2011. He is currently a Ph.D. student at Western Brittany University (UBO), France. He is an assistant professor at the university of Eloued in Algeria. His research interests include a distributed algorithms oriented to the limited resource networks.

References (20)

There are more references available in the full text version of this article.

Cited by (67)

  • Secure and energy aware multi-hop routing protocol in WSN using Taylor-based hybrid optimization algorithm

    2022, Journal of King Saud University - Computer and Information Sciences
View all citing articles on Scopus

Abdelkader Laouid received the MSc. degree in computer science from the University of Bejaia, Algeria, in 2011. He is currently a Ph.D. student at Western Brittany University (UBO), France. He is an assistant professor at the university of Eloued in Algeria. His research interests include a distributed algorithms oriented to the limited resource networks.

Dahmani Abdelnasser professor at university of Tamanghasset, Algeria. Born in 1960 in Algeria, he obtained his Master and PhD degrees of mathematics at the University of Donetsk respectively in 1986 and 1990. He also worked there as assistant professor in the year 1990. He created the team Stochastic Ill-Posed problems at the University of Bejaia in 1995 and earned his title of professor in 2002. He was involved in many research projects concerning inverse problems.

Ahcene Bounceur is an associate professor of Computer Science at the university of Brest (UBO). He is a member of the Lab-STICC Laboratory (MOCS Group). He received a Ph.D. in Micro and nano electronics at Grenoble INP, France in 2007. He received the M.S. degrees from ENSIMAG, Grenoble, France in 2003. From April 2007 to August 2008, he was a postdoctoral fellow at TIMA Laboratory. From September 2007 to August 2008, he was with Grenoble INP, France where he was a temporary professor. He has obtained the 3rd place of the Annual IEEE Test Technology Technical Council (TTTC-IEEE) Doctoral Thesis Contest, VLSI Test Symposium, Berkeley, USA, May 2007. His current research activities are focused in: Tools for physical simulation of Wireless Sensor Networks (WSN), parallel models for accelerating simulations and predicting parameters in WSN, sampling methods for data mining, development of CAT (Computer Aided Test) tools for analog, mixed-signal and RF circuits and statistical modeling of analog, mixed-signal and RF circuits. He is the coordinator of the project ANR PERSEPTEUR and a partner of the project Suidia.

Reinhardt Euler received the Ph.D. degree in mathematics from the University of Cologne. He is a professor of computer science at Lab-STICC laboratory (CNRS 6285), University of Brest. He has held visiting professorships at Grenoble University, the University of British Columbia in Vancouver, and Carnegie Mellon University in Pittsburgh. His research interests include combinatorial algorithms and optimization, graph theory, and the efficient solution of large-scale real- life problem instances.

Farid Lalem is a Ph.D. student at the University of Western Brittany in Brest (France). He received his First cycle diploma, in 2003 from the National Preparatory School to Engineering Studies (Algeria, ENPEI) and conducted his Engineering degree at the polytechnic military school (EMP) in Algeria. His research interests include Wireless Sensor Network reliability, anomaly detection, and insuring data authenticity and integrity in WSN.

Abdelkamel Tari head of LIMED ( laboratory of Medical Computing) since February 2013 and team leader of data mining. He held different positions at the university of Bjaia (Head of Computing department, Operational Rechearch department, head of doctoral school) and at the National School of Computing ESI (ex.INI), Algiers between 1986–1994. After his Diploma in Mathematics at USTHB (Algiers), he held his Master by Research in Lancaster University (England). He defended his PhD Thesis in Computer Sciences in 2008 at the university of Bjaia and his Accrditation to supervise (HDR) at ESI (ex-INI) in 2010.

View full text