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An Analytical Model for Power Control T-MAC Protocol
Abstract
This paper presents a Power Control T- MAC protocol that combines the features from S-MAC and T-MAC protocols for Wireless Sensor Networks (WSN). This protocol has been proposed to reduce the energy consumption of a node. In WSN a node consumes energy in transmitting and receiving of data, listening transmissions of other nodes, and in sleep mode. Therefore, energy consumption of a node has been estimated by adding up the energy consumed in each of the above activity. This has been achieved by estimating the time spent in each activity by a node. The proposed protocol has been simulated using NS-2. The simulation results of Power Control T-MAC shows better energy savings as compared to T-MAC and S-MAC protocol.
... An adaptive non-dominated sorting based genetic algorithm was used to solve the optimization problem. An analytical model of the T-MAC protocol was proposed in [32]. The authors in this paper estimated the length of the active and sleep time of a cycle time assuming that the occurrence of events follows the Poisson distribution. ...
... An adaptive nondominated sorting based genetic algorithm was used to solve the optimization problem. An analytical model of the T-MAC protocol was proposed in [32]. The authors in this paper estimated the length of the active and sleep time of a cycle time assuming that the occurrence of events follows the Poisson distribution. ...
Due to the rapidly growing sensor-enabled connected world around us, with the continuously decreasing size of sensors from smaller to tiny, energy efficiency in wireless sensor networks has drawn ample consideration in both academia as well as in industries' R&D. The literature of energy efficiency in wireless sensor networks (WSNs) is focused on the three layers of wireless communication, namely the physical, Medium Access Control (MAC) and network layers. Physical layer-centric energy efficiency techniques have limited capabilities due to hardware designs and size considerations. Network layer-centric energy efficiency approaches have been constrained, in view of network dynamics and available network infrastructures. However, energy efficiency at the MAC layer requires a traffic cooperative transmission control. In this context, this paper presents a one-dimensional discrete-time Markov chain analytical model of the Timeout Medium Access Control (T-MAC) protocol. Specifically, an analytical model is derived for T-MAC focusing on an analysis of service delay, throughput, energy consumption and power efficiency under unsaturated traffic conditions. The service delay model calculates the average service delay using the adaptive sleep wakeup schedules. The component models include a queuing theory-based throughput analysis model, a cycle probability-based analytical model for computing the probabilities of a successful transmission, collision, and the idle state of a sensor, as well as an energy consumption model for the sensor's life cycle. A fair performance assessment of the proposed T-MAC analytical model attests to the energy efficiency of the model when compared to that of state-of-the-art techniques, in terms of better power saving, a higher throughput and a lower energy consumption under various traffic loads.
... On a given time, either a node or few nodes may transmit out of N number of nodes deployed in the field. Therefore, the probability of a node involved in transmission is [3]. At the initial stage of the network all the nodes are equipped with equal energy. ...
This paper presents a new methodology for energy consumption of nodes and throughput analysis has been performed through simulation for B-MAC protocol in Wireless Sensor Networks. The design includes transmission power control and multi-hop transmission of frames through adjusted transmitted power level. Proposed model reduces collision with contention level notification. The proposed model has been simulated using MATLAB. The simulations reveal better results for throughput of the proposed model as compared to B-MAC protocol. In this model we have included a mechanism for node discovery to find the location of the node before transmission of data to it. This increases the throughput of the network since the position of a dislocated node has been found, that results into successful transmission of frames.However, the energy consumption of a node increases due to energy consumed in node discovery.
This paper presents an analytical model for estimat
ing throughput and energy consumption in Z-MAC
protocol for Wireless Sensor Networks. The analytic
al design includes transmission power control and
transmission of frames through one hop, two hop and
multi hop. Proposed model reduces collision under
low contention level as well as high contention lev
el with the use of explicit contention notification
. The
proposed protocol has been simulated using MATLAB.
The simulations reveal better results for throughpu
t
and energy consumption of the proposed model as com
pared to Z-MAC protoco
This paper presents an analytical model for estimating throughput and energy consumption in Z-MAC protocol for Wireless Sensor Networks. The analytical design includes transmission power control and transmission of frames through one hop, two hop and multi hop. Proposed model reduces collision under low contention level as well as high contention level with the use of explicit contention notification. The proposed protocol has been simulated using MATLAB. The simulations reveal better results for throughput and energy consumption of the proposed model as compared to Z-MAC protocol. KEYWORDS Wireless Sensor Networks, Trigonometry, Possion distribution and Energy efficiency.
In this paper we describe T-MAC, a contention-based Medium Access Control protocol for wireless sensor networks. Applications for these networks have some characteristics (low message rate, insensitivity to latency) that can be exploited to reduce energy consumption by introducing an active/sleep duty cycle. To handle load variations in time and location T-MAC introduces an adaptive duty cycle in a novel way: by dynamically ending the active part of it. This reduces the amount of energy wasted on idle listening, in which nodes wait for potentially incoming messages, while still maintaining a reasonable throughput. We discuss the design of T-MAC, and provide a head-to-head comparison with classic CSMA (no duty cycle) and S-MAC (fixed duty cycle) through extensive simulations. Under homogeneous load, T-MAC and S-MAC achieve similar reductions in energy consumption (up to 98%) compared to CSMA. In a sample scenario with variable load, however, T-MAC outperforms S-MAC by a factor of 5. Preliminary energy-consumption measurements provide insight into the internal workings of the T-MAC protocol.
Power saving is a very critical issue in energy-constrained wireless sensor networks. Many schemes can be found in the literature, which have significant contributions in energy conservation. However, these schemes do not concentrate on reducing the end-to-end packet delay while at the same time retaining the energy-saving capability. Since a long delay can be harmful for either large or small wireless sensor networks, this paper proposes a TDMA-based scheduling scheme that balances energy-saving and end-to-end delay. This balance is achieved by an appropriate scheduling of the wakeup intervals, to allow data packets to be delayed by only one sleep interval for the end-to-end transmission from the sensors to the gateway. The proposed scheme achieves the reduction of the end-to-end delay caused by the sleep mode operation while at the same time it maximizes the energy savings.
Abstract—This letter presents a new approach to evaluate the throughput/delay performance of the 802.11 Distributed Coor- dination Function (DCF). Our approach relies on elementary conditional probability arguments rather than bidimensional Markov chains (as proposed in previous models), and can be easily extended to account for backoff operation more general than DCF’s one. Index Terms—IEEE 802.11, Multiple Access Control, perfor-
Energy consumption is a critical constraint in wireless sensor networks. Focusing on the energy efficiency problem of wireless sensor networks, this paper proposes a method of prediction-based dynamic energy management. A particle filter was introduced to predict a target state, which was adopted to awaken wireless sensor nodes so that their sleep time was prolonged. With the distributed computing capability of nodes, an optimization approach of distributed genetic algorithm and simulated annealing was proposed to minimize the energy consumption of measurement. Considering the application of target tracking, we implemented target position prediction, node sleep scheduling and optimal sensing node selection. Moreover, a routing scheme of forwarding nodes was presented to achieve extra energy conservation. Experimental results of target tracking verified that energy-efficiency is enhanced by prediction-based dynamic energy management.
A wireless sensor network is composed of a great number of sensing devices equipped with limited power sources. Under such battery-based constraints with limited power supply, energy consumption is a key issue for designing sensor network applications. Some sensor products adopt an IEEE 802.11-like MAC protocol. However, IEEE 802.11 MAC is not a good solution for sensor networks. S-MAC (sensor MAC) proposes enhanced schemes, such as periodic sleep and overhearing avoidance, to provide a better choice for sensor applications. The paper presents an analytic model for evaluating the energy consumption at nodes in an S-MAC based wireless sensor network, and we develop an energy consumption analysis under different traffic conditions for distinct network topologies. The proposed model can guide designers to evaluate the energy consumption and determine the corresponding dominating factors. We validate the accuracy of the analytic model by comparing the analytic results with ns-2 simulation results.
In wireless sensor networks (WSNs), sensor nodes are typically battery powered and energy consumption is critical. In this paper we present an efficient transmission power control algorithm based on the RTS/CTS mechanism in SMAC. The main contribution of our work is to introduce a low-cost power controlled transmission of RTS, CTS, DATA, and ACK frames while preserving the collision and overhearing avoidance properties of SMAC protocol. Our proposed algorithm is simulated and the simulation result shows that our algorithm can reduce the energy consumption by 40% - 60% comparing to the conventional SMAC protocol, and outperform the LMA (local mean algorithm) by 20% - 30%.
Spatial backoff has recently been applied for contention resolution in wireless networks as an alternative to algorithms that backoff in time, such as the binary exponential backoff algorithm used in IEEE 802.11. Despite its success in saving energy and increasing spatial reuse, the use of transmission power control in spatial backoff has negative consequences to node throughput fairness. In this paper we study a variant of the hidden terminal problem that arises from link asymmetries, and its impact on the expected node throughput. We give an analytical model that relates throughput to the transmission power level and backoff window size. Using the model we propose a time–space (TS) backoff algorithm with the objective of fair node throughput and incorporate it into a carrier sense multiple access (CSMA) protocol as CSMA/TS. Through simulation we show that CSMA/TS achieves a high fairness index value while attaining good total throughput in most scenarios.
Monitoring applications emerge as one of the most important applications of wireless sensor networks (WSNs). Such applications typically have long-running complex queries that are continuously evaluated over the sensor measurement streams. Due to the limited energy of the sensors in WSNs, energy efficient query evaluation is critical to prolong the system lifetime – the earliest time that the network can not perform its intended task anymore.We model complex queries by expression trees and consider the problem of maximizing the lifetime of a wireless sensor network for the continuous in–network evaluation of an expression trees T, so the value of its root is available at the base station. In-network evaluation means that the evaluation of the operators of T may be pushed to the network nodes, and continuous means the repeated evaluation of T (once at each round). Continuous in-network evaluation of T entails addressing the following two coupled aspects of the problem: (a) the placement of the operators, variables, and constants of T to network nodes and (b) the routing of their values to the appropriate network nodes that needed them to evaluate the operators.We analyze the complexity and provide a simple and effective algorithm for the placement of the nodes of T onto the sensor nodes of a WSN. Our algorithm of operator placement attempts to minimize the total amount of data that need to be communicated. A placement of T induces a certain Maximum Lifetime Concurrent Flow (mlcf) problem. We provide an efficient algorithm that finds near-optimal integral solutions to the mlcf problem, where a solution is a collection of paths on which certain amount of integral flow is routed. Our approach to the continuous in-network evaluation of T consists of utilizing both our placement and routing algorithms above.We demonstrate experimentally that our approach consistently and effectively find the maximum lifetime solutions for the continuous in-network evaluation of expression trees in wireless sensor networks.
We investigate the problem of sleep/wake scheduling for low duty cycle sensor networks. Our work differs from prior work in that we explicitly consider the effect of synchronization error in the design of the sleep/wake scheduling algorithm. In our previous work, we studied sleep/wake scheduling for single hop communication, e.g., intra-cluster communication between a cluster head and cluster members. We showed that there is an inherent trade-off between energy consumption and message delivery performance (defined as the message capture probability). We proposed an optimal sleep/wake scheduling algorithm, which satisfies a given message capture probability threshold with minimum energy consumption.In this work, we consider multi-hop communication. We remove the previous assumption that the capture probability threshold is already given, and study how to decide the per-hop capture probability thresholds to meet the Quality of Services (QoS) requirements of the application. In many sensor network applications, the QoS is decided by the amount of data delivered to the base station(s), i.e., the multi-hop delivery performance. We formulate an optimization problem to set the capture probability threshold at each hop such that the network lifetime is maximized, while the multi-hop delivery performance is guaranteed. The problem turns out to be non-convex and hence cannot be efficiently solved using standard methods. By investigating the unique structure of the problem and using approximation techniques, we obtain a solution that provably achieves at least 0.73 of the optimal performance. Our solution is extremely simple to implement.
Communication is usually the most energy - consuming event in wireless sensor networks (WSNs). The lifetime of these networks is determined by the capacity of batteries and one of the biggest challenges is to reduce the energy consumed in the communication. Several techniques to reduce the energy consumption have been proposed in routing protocols: diminish the traffic of data, optimize the routes or the control of the topology. However, the management and operation of the node's radio is responsibility of the medium access control (MAC) protocol. This thesis presents four new transmission power control (TPC) techniques for MAC protocols in WSNs. These techniques are based on the interaction between sensor nodes and take into account the limitations of resources such as processing, memory and energy in the calculation of the minimum of transmission power. To evaluate these techniques, four MAC protocols had been developed: iterative, attenuation, AEWMA and hybrid. The Iterative was the first MAC protocol with TPC developed exclusively for WSN. These protocols have been experimented in the Mica Motes2 platform, in diverse scenarios varying parameters such as internal and external environment, the distance among the communicating nodes, the occurrence of simultaneous transmissions, the use of multi-hop transmissions and node mobility. Results have shown that TPC protocols reduce the energy consumption by up to 57% in comparison to the protocols with fixed transmission power. Moreover, the protocols with TPC increase the throughput of the network while maintaining a very high delivery rate.
We propose an OS-directed power management technique to improve
the energy efficiency of sensor nodes. Dynamic power management (DPM) is
an effective tool in reducing system power consumption without
significantly degrading performance. The basic idea is to shut down
devices when not needed and wake them up when necessary. DPM, in
general, is not a trivial problem. If the energy and performance
overheads in sleep-state transition were negligible, then a simple
greedy algorithm that makes the system enter the deepest sleep state
when idling would be perfect. However, in reality, sleep-state
transitioning has the overhead of storing processor state and turning
off power. Waking up also takes a finite amount of time. Therefore,
implementing the correct policy for sleep-state transitioning is
critical for DPM success. It is argued that power-aware methodology uses
an embedded microoperating system to reduce node energy consumption by
exploiting both sleep state and active power management
This paper proposes S-MAC, a medium-access control (MAC) protocol designed for wireless sensor networks. Wireless sensor networks use battery-operated computing and sensing devices; a network of these devices will collaborate for a common application such as environmental monitoring. We expect sensor networks to be deployed in an ad hoc fashion, with individual nodes remaining largely inactive for long periods of time, but then becoming suddenly active when something is detected. These characteristics of sensor networks and applications motivate a MAC that is different from traditional wireless MACs such as IEEE 802.11 in almost every way: energy conservation and selfconfiguration are a primary goals, while per-node fairness and latency are less important. S-MAC uses three novel techniques to reduce energy consumption and support selfconfiguration. To reduce energy consumption in listening to an idle channel, nodes periodically sleep. Neighboring nodes form virtual clusters to auto-synchronize on sleep schedules. Inspired by PAMAS [10], S-MAC also sets the radio to sleep during transmissions of other nodes. Unlike PAMAS, it only uses in-channel signaling. Finally, S-MAC applies message passing to reduce contention latency for sensor-network applications that require store-and-forward processing as data moves through the network. We evaluate our implementation of S-MAC over a sample sensor node, the Mote, developed at University of California, Berkeley (UCB). The experiment results show that, on a source node, an 802.11-like MAC consumes 2--6 times more energy than S-MAC for traffic load of 1--10s/message. Keywords--- Medium Access Control, Wireless Networks, Sensor Networks I.
This paper presents a power control MAC protocol that allows nodes to vary transmit power level on a per-packet basis. Several researchers have proposed simple modifications of IEEE 802.11 to incorporate power control. The main idea of these power control schemes is to use different power levels for RTS-CTS and DATA-ACK. Specifically, maximum transmit power is used for RTS-CTS, and the minimum required transmit power is used for DATA-ACK transmissions in order to save energy. However, we show that these schemes can degrade network throughput and can result in higher energy consumption than when using IEEE 802.11 without power control. We propose a power control protocol which does not degrade throughput and yields energy saving.