Analysis on the energy consumption in stochastic wireless networks

The green communication draws a lot of attention in recent years. Meanwhile, as a promising technology, cognitive radio will constitute an important part of the future communication networks. Energy consumption of cognitive radio network is worthy studying, which is analyzed in this paper applying stochastic network calculus. A multi-channel cognitive radio network model is introduced. Stochastic network calculus is then used in the analysis, which is a newly developed theory dealing with queuing system found in computer networks. Guaranteed service for secondary users is firstly derived, followed by stochastic service curve derivation. Then, minimum transmission rate is conducted which is an important variable in energy analysis. After that, relationship between energy consumption and transmission rate is presented. As part of the derivation, delay bound and transmission power are discussed. Finally, numerical results of transmission rate, transmission power and energy consumption are shown for different constraint, where the influence of channel quantity is further discussed.

The capacity and geographical coverage of the global communications network continue to expand. One consequence of this expansion is a steady growth in the overall energy consumption of the network. This is the first of two papers that explore the fundamental limits on energy consumption in optical communication systems and networks. The objective of these papers is to provide a framework for understanding how this growth in energy consumption can be managed. This paper (Part I) focuses on the energy consumption in optically amplified transport systems. The accompanying paper (Part II) focuses on energy consumption in networks. A key focus of both papers is an analysis of the lower bound on energy consumption. This lower bound gives an indication of the best possible energy efficiency that could ever be achieved. The lower bound on energy in transport systems is limited by the energy consumption in optical amplifiers, and in optical transmitters and receivers. The performance of an optical transport system is ultimately set by the Shannon bound on receiver sensitivity, and depends on factors such as the modulation format, fiber losses, system length, and the spontaneous noise in optical amplifiers. Collectively, these set a lower bound on the number of amplifiers required, and hence, the amplifier energy consumption. It is possible to minimize the total energy consumption of an optically amplified system by locating repeaters strategically. The lower bound on energy consumption in optical transmitters and receivers is limited by device and circuit factors. In commercial optical transport systems, the energy consumption is at least two orders of magnitude larger than the ideal lower bounds described here. The difference between the ideal lower bounds and the actual energy consumption in commercial systems is due to inefficiencies and energy overheads. A key strategy in reducing the energy consumption of optical transport systems will be to reduce these inefficiencies and overheads.

Multimedia application integrates a variety of media, namely, audio, video, images, graphics, text, and data, each of which have different quality of service (QOS) requirements. In this paper we evaluate the support of reservation-based high speed protocols including DQDB (distributed queue dual bus), CRMA (cyclic-reservation multiple-access), DQMA (distributed-queue multiple-access), and FDQ (fair distributed queue), for various multimedia traffic including low and medium quality video, high quality MMPEG video, and data traffic. Through extensive experiments, we vary different traffic and protocol parameters including transmission rate, delay and loss constraint, data load and data burstiness, to determine the number of multimedia sessions supported by each of the four protocols. Delay constraints have moderate effect on some of the protocols, but loss constraints have very little effect on any protocol. Bursty data significantly degrade real-time traffic performance, but the negative effect is almost corrected when delay constraint is somewhat relaxed. These results show that the reservation-based protocols are suitable for integrating real-time multimedia traffic with bursty data traffic in very high speed network, especially when delay constraint is somewhat relaxed. Due to its excellent fairness, FDQ clearly stands out to be the best protocol among four to support heterogeneous traffic.

Multi-carrier relay selection is of particular interest and challenge due to the spatio-frequency coupling and the dynamics of available spectral and relay resources. Among a number of promising relay selection schemes, combined relay selection stands out as an equilibrium between system complexity and reliability. Recent research progress has witnessed the capability of neural computing as a powerful tool to efficiently realize combined relay selection for a given network topology where the number of relays and their locations are fixed and known. However, for contemporary wireless networks that are highly dynamic, the classic neural computing methods can hardly help out because of the scale drifts of input and output matrices. To enable multi-carrier combined relay selection in stochastic wireless networks (SWNs) where the number of available relays for selection could vary, we propose a recurrent neural network (RNN) based framework and devise several training methods suited for various application scenarios. In addition, we conduct a set of computer experiments to verify the effectiveness and efficiency of the proposed RNN-based framework compared with several baselines. With the obtained experimental results, we also evaluate and discuss the proposed framework's reliability, generalization ability, and the robustness against imperfect channel state information (CSI).

Wireless sensor “motes” is small or tiny embedded systems equipped with radios for wireless communication in the networks, which depend on batteries as a power source. The development of Medium Access Control (MAC) protocols which search is for to minimize the energy consumption in the wireless sensor network. Recent contention based MAC protocols reduce energy usage by placing the radio in a low power sleep state when not sending or receiving the message. In this paper the main emphasis is on the analysis of the Contention Based MAC Protocols and energy consumption in the networks. Based on the work done by various researchers conclude that S-MAC is the backbone of all the MAC protocols for wireless sensor networks. Our proposed work investigated the energy usage and compared the performance of IEEE 802.11 MAC protocol with S-MAC protocol on different modes like without periodic sleep and with periodic sleep on different performance metrics like Remaining Energy vs Time, Energy consumption vs global packet id and Average End to End Delay vs Time. The performance of S-MAC protocol improves on the basis of duty-cycle parameter, which determines the length of sleep period in a frame and this parameter is a variable. So changing the duty cycle will change the performance of S-MAC protocol. Finally, we have used the different routing protocol with S-MAC to evaluate the energy consumption. The experimented worked done on Network Simulator Ns2- 2.34.KeywordsMedium Access ProtocolWireless Sensor NetworkIdle listeningSleep StateS-MACEnergy ConsumptionDuty cycle

Wireless Sensor Networks use battery-operated computing and sensing devices. It is often impractical or even impossible to charge/replace the exhausted batteries of the nodes. Thus, energy consumption is the main concern in a wireless sensor network. Moreover, a critical event detected by the sensor network should be delivered to the user as soon as possible. Thus, for sensor networks, both energy efficiency and transmission latency are important parameters. In this paper, we propose a novel asynchronous, duty cycled, energy efficient, and low transmission delay for wireless sensor networks, which addresses all the sources of energy waste to make the medium access more energy efficient, while keeping transmission delay low.The currently available asynchronous contention-based MAC protocols require that proper strategies for sender and receiver nodes are provided to rendezvous. However, the proposed protocol does not rely on any rendezvous between sender and receiver. For evaluating the novel MAC protocol, we have simulated this protocol and two very efficient and established MAC protocols, RTS/CTS IEEE 802.11 and S-MAC. The simulation results indicate that the proposed protocol has very good performance. In addition, as the results show, the novel protocol provides a very suitable balance between energy efficiency and transmission delay.

This is Part II of a two-part paper that explores the fundamental limitations on energy consumption in optical communications. Part I covers energy consumption in optical transport. Part II explores the lower bound on energy consumption in optical switches and networks, analyzes the energy performance of a range of switching devices, and presents quantitative models of the lower bounds on energy consumption in these devices. These models are incorporated into a simple model of a global switched network and the lower bound on total network energy consumption is estimated. We compare the results of this bottom-up calculation of the lower bound on network energy with a previous top-down analysis of overall network energy consumption based on real-world data for state-of-the art equipment and “business-as-usual” forward projections. The present analysis confirms a previous finding in that in a global scale network, the energy consumption of the switching infrastructure is larger than the energy consumption of the transport infrastructure. We find that the theoretical lower bounds on transport energy identified in Part I and the switching energy in this paper are more than three orders of magnitude lower than predicted by a “business-as-usual” analysis. In this paper, we explore how the gap between the theoretical lower bounds on energy consumption and current trends in network energy efficiency can be closed. We argue that future research needs to focus on improving the energy efficiency of switching and on devising methods to reduce the quantity of switching infrastructure in the network. Further key strategies for reducing network energy consumption include developing of low-energy transport technologies, reducing the energy overheads associated with peripheral functions that are not central to the transport and switching of data, and reducing the energy consumption of the access network.

Decentralized optimization, particularly the class of decentralized composite convex optimization (DCCO) problems, has found many applications. Due to ubiquitous communication congestion and random dropouts in practice, it is highly desirable to design decentralized algorithms that can handle stochastic communication networks. However, most existing algorithms for DCCO only work in networks that are deterministically connected during bounded communication rounds, and therefore cannot be extended to stochastic networks. In this paper, we propose a new decentralized dual averaging (DDA) algorithm that can solve DCCO in stochastic networks. Under a rather mild condition on stochastic networks, we show that the proposed algorithm attains <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">global linear convergence</i> if each local objective function is strongly convex. Our algorithm substantially improves the existing DDA-type algorithms as the latter were only known to converge <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">sublinearly</i> prior to our work. The key to achieving the improved rate is the design of a novel dynamic averaging consensus protocol for DDA, which intuitively leads to more accurate local estimates of the global dual variable. To the best of our knowledge, this is the first linearly convergent DDA-type decentralized algorithm and also the first algorithm that attains global linear convergence for solving DCCO in stochastic networks. Numerical results are also presented to support our design and analysis.

This paper presents a scalability analysis over a novel integer programming model devoted to optimize power consumption efficiency in heterogeneous wireless sensor networks. This model is based upon a schedule of sensor allocation plans in multiple time intervals subject to coverage and connectivity constraints. By turning off a specific set of redundant sensors in each time interval, it is possible to reduce the total energy consumption in the network and, at the same time, avoid partitioning the whole network by losing some strategic sensors too prematurely. Since the network is heterogeneous, sensors can sense different phenomena from different demand points, with different sample rates. As the problem instances grows the time spent to the execution turns impractcable.

Today main objective of wsn is to minimize the energy dissipation for the whole network. Clustering is one of the most knows methods widely used to face these challenges. Fix Cluster Head Selection (FCHS) routing protocol analyses how the system lifetime is improved by fixing the selection of clusters head. In this paper a cluster based communication protocol with considering the low energy consumption in wireless sensor networks, is introduced which balanced the energy load among the sensor node. Fix Cluster Head Selection (FCHS) analyses the cluster head selection to find the optimal probability of becoming a cluster head. Simulation result of FCHS corresponding to LEACH in mat lab shows that these designs increase the lifetime of the network 105 %. We found that FCHS yield longer stability region for higher values of extra energy brought by more powerful nodes. Finally, LEACH protocol and the improved algorithm simulate in MATLAB, and make Performance analysis and comparison in number of nodes alive, total energy consumption in network and a round of node death distribution. The results show that, FCHS compared with LEACH protocol, the improved algorithm prolongs the network life cycle, raises energy utilization and has good load balance.

The number of Machine-to-Machine (M2M) devices has increased massively in the last few years and will continue to increase in the years to come. Spectrum utilisation efficiency and energy efficiency are the main challenges and design goals for M2M networks. Cognitive radio (CR) is a promising technology that can address these challenges. In this paper, the authors have proposed and developed an energy efficient mechanism to reduce energy consumption in Cognitive M2M (CM2M) networks. Their solution guarantees the throughput and reliability constraints for CM2M Devices (CM2MDs). The proposed mechanism can reduce energy consumption in CM2M networks by exploiting efficient sensing and accessing schemes for CM2MDs. The authors further develop sleep-mode/switching and accessing techniques to work efficiently with the proposed mechanism. The simulation results show that the proposed mechanism guarantees a desirable throughput and reduces overall energy consumption in the network.

It is a very important topic to reduce network energy consumption for constructing green network in current computing area. Rate adaptation of network device provides an effective approach to optimize network energy consumption and improve network energy efficiency. In this paper, we propose a global optimization approach for network energy efficiency based on rate adaptation. According to the characteristics of service in network system, we establish an energy consumption model by abstracting network service components as a processing domain from a global point of view. In order to obtain the average rate of service and the switched number of running mode in processing domain, the service process of the processing domain is regarded as the queuing system with variable service rate. Then, we construct energy consumption optimization model to minimize network energy consumption. We give a genetic algorithm to solve energy consumption optimization model, and the comparison results of energy consumption and delay in simulation. Compare with the two GreenOSPF energy efficiency algorithms with rate adaptation in simulation, the energy consumption optimization model proposed by this paper is suitable for rate adaptation mechanism at link, and then obtain the goal of optimization and reducing of energy consumption.

A game-theoretic approach for studying power control in multiple-access networks with transmission delay constraints is proposed. A non-cooperative power control game is considered in which each user seeks to choose a transmit power that maximizes its own utility while satisfying the user's delay requirements. The utility function measures the number of reliable bits transmitted per joule of energy and the user's delay constraint is modeled as an upper bound on the delay outage probability. The Nash equilibrium for the proposed game is derived, and its existence and uniqueness are proved. Using a large-system analysis, explicit expressions for the utilities achieved at equilibrium are obtained for the matched filter, decorrelating and minimum mean square error multiuser detectors. The effects of delay constraints on the users' utilities (in bits/Joule) and network capacity (i.e., the maximum number of users that can be supported) are quantified.

Recently, the cooperative communication has been explored more and more as an impressing technique to combat the effects of channel fading and to reduce the energy consumption in wireless networks. However, the impact of cooperative communications on transmission rate has not been well-addressed yet. In this paper, we provide an analytical framework for transmission rate enhancement issue in wireless communications. For a given transmit power and a desired probability of success, we investigate how much average transmission rate can be increased by cooperative communications. Three transmission models have been compared: the direct transmission, the cooperative transmission without maximal ratio combiner (MRC), and cooperative transmission with MRC. The analytical and numerical results show that around 1 - 3b/s/Hz transmission rate can be improved when the source-destination distance is 20m. We also reveal that the MRC scheme is not always beneficial, especially when the source-destination distance is short and the relay is close to the destination.

The aim is to solve the problems of communication and positioning of the lunar robots without GPS and network base stations, improving communication efficiency and reducing communication energy consumption. A multi-robot communication routing optimization algorithm combined with Lora positioning is proposed. The algorithm combines Lora positioning technology and multi-robot communication routing optimization technology to dynamically update the distance information between robot groups. The Floyd algorithm with improved weight value is used to find the communication path with the lowest energy consumption and the highest transmission efficiency between robots. It enables each robot to transmit information along the optimal path, thereby effectively reducing the length of the transmission path and the corresponding network delay, and expanding the range of robot activities.. Simulation results show that the algorithm effectively reduces the network delay compared with the classic AODV (Ad Hoc on-demand distance vector) protocol and LEACH (Low Energy Adaptive Clustering Hierarchy) protocol, and effectively reduces the overall network energy consumption, avoiding robot groups Energy hole problem.