تجارت کردن بین انرژی و تاخیر در انتشار اطلاعات در شبکه های حسگر بی سیم با استفاده از برش محدوده انتقال

Data dissemination is an essential function in wireless sensor networks (WSNs). A WSN consists of a large number of unattended sensors with limited storage, battery power, computation, and communication capabilities, where battery power (or energy) is the most crucial resource for sensor nodes. Because delay time is also a critical metric for certain applications, data dissemination between source sensors (or simply sources) and a sink (or central gathering point) should be done in an energy-efficient and timely manner. In this paper, we present an approach that characterizes a trade-off between energy and source-to-sink delay (or simply delay). Specifically, we decompose the transmission range of sensors into concentric circular bands (CCBs) based on a minimum transmission distance between any pair of sensors. Our decomposition strategy provides a classification of these CCBs that helps a sensor express its degree of interest (DoI) in minimizing two conflicting metrics, namely energy consumption and delay. We also propose a data dissemination protocol that exploits the above-mentioned decomposition to meet the specific requirements of a sensing application in terms of energy and delay. We prove that the use of sensors nodes, which lie on or closely to the shortest path between a source and a sink, as proxy forwarders in data dissemination from sources to a sink, helps simultaneously minimize energy consumption and delay. Also, we compute theoretical lower and upper bounds on these two metrics. Our simulation results are found to be consistent with our theoretical results, and show that the first CCB minimizes energy consumption; the last CCB minimizes delay; and the middle CCBs trade-off energy consumption with delay in data dissemination in WSNs.

A wireless sensor network (WSN) is composed of a large number of sensor nodes that communicate with each other possibly through multi-hop wireless links despite the absence of any fixed administration or established infrastructure. They also collaborate to collect data during monitoring an environment and disseminate them to a central gathering point, called the sink (or base station). Sensor networking technology, however, faces a critical problem due to the limited energy, storage, sensing, communication, and computation capabilities of sensors. Because data dissemination is a vital function in WSNs, optimized protocols should be designed to guarantee an efficient operation of the network by extending its lifetime and providing the sink with sensed data in a timely manner for further analysis and processing. Therefore, it is necessary to minimize the energy consumption and delay when disseminating data packets collected by sources towards the sink. Battery power (or energy) is the most crucial resource for sensors, and particularly in certain environments, such as battlefields, where replacing or recharging batteries is difficult or even impossible. In addition, some sensing applications require fast response-time, which imposes some bounds on delay. On the one hand, the energy consumption is dominated by the transmission energy Etx, which is proportional to the distance d between transmitter and receiver, i.e., Etx ∝ dα, where 2 ⩽ α ⩽ 4 is the path loss exponent. Hence, minimizing the energy consumption could be done by minimizing the distance d. On the other hand, delay is proportional to the number of forwarders on the dissemination path between a source and the sink. Therefore, in order to minimize delay, it is necessary to minimize the number of forwarders, which in turn could be achieved by maximizing the distance between consecutive forwarders. Thus, finding a trade-off between energy consumption and delay seems to be very appealing as they represent two conflicting metrics. This paper presents a study of the trade-off between energy consumption and delay based on the idea of decomposing the transmission range of sensors into concentric circular bands (CCBs) when building dissemination paths between sources and the sink. A dissemination path is a set of segments forming a chain of proxy forwarders. This decomposition is based on a minimum transmission distance between any pair of proxy forwarders which we computed analytically. Because sensors are densely and uniformly distributed in a sensor field, every CCB contains a subset of sensors as potential proxy forwarders. Our proposed data dissemination protocol trades off energy consumption with delay using a classification of the obtained CCBs. This classification enables a sensor to specify its degree of interest (DoI) in energy consumption and delay. The main contributions of this paper can be summarized as follows: (i) We propose a novel data dissemination protocol that trades off energy consumption with delay at different levels by decomposing the transmission range of sensors into CCBs and classifying them. These levels could favor minimizing energy consumption or delay, or trade-off between them. We also provide extensive simulations that help sensing application designers gain more insight on how to trade-off energy consumption with delay. (ii) We prove that the selection of sources as proxy forwarders which lie on or closely to the shortest path between source and sink yields minimum energy consumption and delay. (iii) We compute lower and upper bounds on energy consumption and delay based on the above-mentioned transmission range decomposition approach. The remainder of this paper is organized as follows. Section 2 reviews a sample of energy-efficient data dissemination protocols for WSNs. Section 3 discusses our proposed protocol which trades off energy consumption with delay. Theoretical and simulation results are presented in Section 4. Simulation results are presented in Section 5. Section 6 concludes the paper.

In this paper, we have proposed a novel data dissemination protocol for WSNs, which trades off energy with delay. By decomposing the transmission range of sensors into concentric circular bands (CCBs) and classifying them, a source is enabled to specify its degree of interest (DoI) in minimizing energy consumption and/or delay. Specifically, a given DoI is expressed in terms of a particular CCB. The set of CCBs can be classified into three categories: the first subset favors energy consumption minimization; the second subset favors delay minimization; the third subset minimizes both energy consumption and delay simultaneously. Moreover, each of the first two subsets of CCBs could be further classified depending on how high the DoI given to either metric, which in turn depends on the underlying sensing application. Moreover, we have computed lower and upper bounds on these two metrics and show how to trade-off energy consumption with delay when both metrics are considered for minimization. We proved that choosing sources as proxy forwarders that lie on or closely to the direct path between source and sink leads to maximum energy savings and minimum delay. Regardless of the DoI specified by the source, the proposed protocol selects sensors with maximum remaining energy and whose location is close to the shortest path between source and sink, as proxy forwarders. The rationale behind this decision is to increase the lifetime of individual sensors and hence the operational lifetime of WSNs. Furthermore, the different simulations that we conducted helped us gain more insight on how to trade-off energy consumption with delay and showed consistency with theoretical results. Our future work is threefold. We should notice that static sink based solutions suffer from a problem related to battery power depletion of sensors nearer the sink. Sink mobility would be an alternative solution to this problem as the neighborhood of a mobile sink would vary over time as the sink moves in the field. Our first concern is to extend our proposed protocol to deal with a mobile sink instead of a fixed one. Second, we plan to extend our work by considering joint duty-cycling and data dissemination. Indeed, the assumption that sensors are on all the times is not valid [16]. In order to save energy, it is important that sensors be duty-cycled. Third, we plan to implement the proposed data dissemination protocol with respect to different DoIs and using a real testbed of sensors.