Elsevier

Computer Communications

Volume 31, Issue 9, 8 June 2008, Pages 1763-1776
Computer Communications

The tradeoff between maximizing the sensor network lifetime and the fastest way to report reliably an event using reporting nodes’ selection

https://doi.org/10.1016/j.comcom.2007.11.020Get rights and content

Abstract

Energy-efficiency is one of the major concerns in wireless sensor networks since it impacts the network lifetime. In this paper, we investigate the relationship between sensor networks performance, particularly its lifetime, and the number of reporting nodes N by using both analytical and simulation approaches. We first show that the network lifetime and the number of correctly received reports increase when N decreases. Moreover, we demonstrate that the average time required to report an event is a convex function of N. Based on these results, and as a main contribution, we prove that the optimal number of reporting nodes minimizing the energy consumption in the network does not correspond to the optimal number of reporting nodes allowing the fastest way to report an event. The tradeoff between these two requirements is therefore specific to each sensor application, depending on its particular needs. In this paper, we provide a simple methodology to achieve this tradeoff.

Introduction

Energy-efficiency is a critical issue in wireless sensor networks (WSNs) due to the limited capacity of the sensor nodes’ batteries [1]. Indeed, once a WSN is in place, its lifetime must last as long as possible based on the initially provided amount of energy. In view of this, techniques minimizing energy consumption are required to improve the network lifetime. A widely employed mechanism is to schedule sensor nodes activity so that redundant nodes enter the sleep mode as often as possible [2], [3]. Based on this concept, several energy-efficient MAC protocols [4], [5], [6] and energy-efficient routing protocols [7], [8] have been proposed. Additional solutions, based on congestion control, to reduce energy consumption are also proposed in [9], [10]. These mechanisms aim at achieving further energy conservation by reducing the energy wastage due to the frequently occurring collisions in WSN networks.

The majority of previous works focused mainly on the energy minimization problem. However, minimizing the energy consumption must be achieved while respecting the specific QoS requirements of sensor applications, such as the maximum tolerable time to report an event, and the required event reliability, etc. Indeed, the key performance metrics in WSN networks are both the network lifetime and the average time required to report reliably an event. The optimal solution must therefore take into account these two metrics. In view of this, in this paper, we focus on the analysis of this tradeoff.

Moreover, the current studies handled the energy optimization issue without paying attention to the impact of the number of reporting nodes on the WSN performances. In other words, given a reporting frequency, how the network lifetime and the reporting latency evolve with respect to the number of active reporting nodes? Our work is motivated by the results in [11], [12], which highlight the significant energy conservation that could be achieved when spatial and temporal correlation is exploited to reduce the number of redundant packet transmission in the network. Specifically, a new MAC protocol is proposed in [12] to regulate the network access by limiting the reporting tasks of an observed event to a minimum number of sensor nodes subject to reliability constraints.

In this paper, we present an in-depth analysis of the impact of the number of selected reporting nodes on the WSN performances (i.e., network lifetime, reporting latency). Our ultimate goal is to determine the optimal number of reporting nodes that both minimizes the energy required to report reliably an event and respect the latency constraints. The obtained result can be thus used to parameterize the MAC protocol proposed in [12], which can be seen as the feasibility demonstration of the basic access nodes selection method, to achieve the energy-reliability-latency tradeoffs.

Moreover, in our study, we relax the minimum boundary constraint on the number of reporting nodes entailed by Vuran and Akyildiz [12], by allowing the selected reporting nodes to transmit redundant information (multiple reports). Doing so, further flexibility and thus additional energy conservation could be achieved by our proposal. To the best of our knowledge, we are the first to tackle the energy optimization problem from this perspective while considering the energy-reliability-latency tradeoffs.

To achieve this, we develop new analytical models to explore the relationship between the WSN performances (i.e., network lifetime, event reporting time) and the number of active reporting nodes, given a predefined network reporting frequency. Specifically, we analyze the basic access mechanism of IEEE 802.11 DCF (distributed coordination function) with its optional request-to-send/clear-to-send (RTS/CTS) scheme [13]. This basic protocol is used by the currently deployed WSNs to arbitrate access, among multiple sensor nodes, to the shared medium in order to communicate with the sink node. We first derive the expression of the collision probability and the average energy required to report reliably an event as functions of the number of reporting nodes and the reporting frequency. Based on these results, and as a first main contribution of this paper, we prove that the network lifetime increases when decreasing the number of active reporting nodes. We show that the maximal network lifetime is achieved when only one reporting node is activated while the remaining nodes undergo the sleep mode. Indeed, in doing so, collisions among reporting nodes is avoided, eliminating thus unnecessary energy consumption. We then show analytically that the time required to report an event is a convex function of the number of active reporting nodes N, where the minimum is obtained for Nopt>1. Consequently and as a second main contribution, we demonstrate that the fastest way to report reliably an event does not necessarily lead to the most efficient energy consumption. The tradeoff between these two requirements (i.e., energy consumption and reporting time) depends mainly on the specific QoS needs of the sensor application.

Finally, in order to assess the accuracy of our proposed analytical model, we conduct simulations. To do so, we develop our own evaluation environment using NS-2 [14]. The results show a good match between simulations and the analytical expressions, which confirms the accuracy of our models. The rest of the paper is organized as follows. Section 2 discusses the related works and Section 3 presents the general problem statement. Communications among sensor nodes will be outlined in Section 4. In Section 5, we introduce the mathematical models to evaluate the impact of the number of reporting nodes on the WSN performances. Analytical and simulation results are discussed in Section 6. In Section 7, we provide a simple methodology to achieve the tradeoff between energy consumption and event reporting latency. Finally, Section 8 concludes this paper.

Section snippets

Related work

As stated before, in order to minimize the energy consumption in WSNs, several energy-efficient MAC protocols [4], [5], [6] and energy-efficient routing protocols [7], [8] have been proposed in the literature. These schemes aim to decrease the energy consumption by using sleep schedules. The key idea behind this concept is to turn off completely some parts of the sensor circuitry (e.g., microprocessor, memory, radio) when it does not receive or transmit data, instead of keeping the sensor node

Problem statement

Let us consider the WSN as depicted in Fig. 1. In essence, a WSN ensures the supervision of a given area by the use of a sink node, which collects reports from the network. In this analysis we consider event detection driven wireless sensor applications. In other words, communications are triggered by the occurrence of a pre-specified type of events. Once an event occurs, it has to be reported to the sink by the sensor nodes. In such network, sensor nodes, within an event radius Rc, are the

Wireless sensor networks

As stated before, communications in currently deployed WSN are carried using the basic IEEE 802.11 DCF protocol and its optional RTS/CTS mechanism. Specifically, once an event is detected, the N active reporting nodes compete to access the common data channel to report the event to the sink. The IEEE 802.11 DCF access method is based on the CSMA/CA technique. Accordingly, a host, wishing to transmit a frame, first senses the channel activity until an idle period equal to Distributed Inter Frame

Performance analysis

In this section, we present mathematical models to derive both the WSN lifetime and the average time required to report an event, as functions of the number of reporting nodes N and the reporting frequency f. To achieve this, we first calculate the collision probability in such networks caused by the multiple reporting nodes. Then, we derive the average time required to report reliably an event (i.e., to transmit R reports). Based on this result, we can easily obtain the associated consumed

Performance evaluation

In this section, we evaluate the impact of the reporting nodes on the WSN performances using both analytical and simulation approaches. The simulations are run on NS-2 simulator [14].

In our simulations, we have not assumed the mobility of the sensor nodes. Therefore, the topology does not continuously vary with time during simulations. However, we note that the sensor nodes may die due to energy depletion leading to variation in overall topology. As stated before, the IEEE 802.11 DCF MAC

Tradeoff between energy and latency

Energy-efficiency is a critical issue in wireless sensor networks. However, minimizing the energy consumption in such networks must be achieved while respecting the maximum tolerable time to report an event. The optimal solution must therefore take into account these two metrics.

In this section, we propose a simple function fchoice to determine the optimal number of reporting nodes Nopt that achieves the above-mentioned tradeoff. For illustration purposes, we give hereafter the expression of f

Conclusion

In this paper, we explored the relationship between the wireless sensor network performance and the number of reporting nodes. To the best of our knowledge, we are the first to investigate the energy optimization problem from this perspective. Accordingly, we demonstrated that the optimal number of reporting nodes that minimizes the energy expenditure in the sensor network does not correspond to the fastest way to report an event. Based on this result, we propose a simple methodology to achieve

References (20)

  • M.C. Vuran et al.

    Spatio-temporal correlation: theory and applications for wireless sensor networks

    Computer Networks Journal (Elsevier)

    (2004)
  • I. Akiyldiz et al.

    A survey on sensor networks

    IEEE Communication Magazine

    (2002)
  • S. Singh et al.

    PAMAS: power aware multi-access protocol with signaling for ad hoc networks

    ACM Computer Communication. Review

    (1998)
  • F. Dai, J. Wu, Distributed dominant pruning in ad hoc wireless networks, in: Proceedings of IEEE International...
  • M. Miller et al.

    A mac protocol to reduce sensor network energy consumption using a wake-up radio

    IEEE Transactions on Mobile Computing

    (2005)
  • W. Ye et al.

    Medium access control with coordinated adaptive sleeping for wireless sensor networks

    IEEE/ACM Transactions on Networking

    (2004)
  • T. van Dam, K. Langendoen, An adaptive energy-efficient MAC protocol for wireless sensor networks, in: Proceeding of...
  • R.C. Shah, H.M. Rabaey, Energy aware routing for low energy ad hoc sensor networks, IEEE Wireless Communication and...
  • J. Chang et al.

    Maximum lifetime routing in wireless sensor networks

    IEEE Transactions on Networking

    (2004)
  • S. Tilak, N.B Abu-Ghazaleh, W. Heinzelman, Infrastructure tradeoffs for sensor networks, in: Proceedings of ACM WSNA...
There are more references available in the full text version of this article.

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