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In this paper, we consider a computation offloading problem in a three-tier network consisting of multiple mobile users (MUs), multiple edge clouds, and a central cloud. On this basis, we formulate a system Energy Time Cost ($ETC$) minimization problem by jointly optimizing the resource allocation, mobile-edge matching decision, and offloading decision. Due to the difficulty of directly solving the formulated problem, we decompose it and propose two offloading algorithms, namely Gale-Shapley based Minimum/Sequential Offloading Algorithm (GS-MOA/GS-SOA), to optimize offloading decisions by minimizing the system $ETC$ , in which the mobile-edge matching strategies based on the proposed Gale-Shapley based Mobile-Edge mAtching aLgorithm (GS-MEAL) and resource allocations are optimized iteratively. The simulations show the effectiveness of our proposed algorithm. [ABSTRACT FROM AUTHOR]

Next-generation wireless communications are expected to provide reliable high-rate connectivity. The recent concept of fog-enabled architecture comes to rescue by invoking a substantial amount of data storage close to end-user devices for meeting these challenges. Thus, caching popular contents at heterogeneous devices, e.g., fog nodes (FNs) or fog access points (FAPs), constitutes a promising technique of reducing both the traffic and the energy consumption of the backhaul links. Therefore, in this paper, we propose an energy-efficient caching and node association algorithm for cache-aided fog networks. First, we solve the problem of energy-efficient content caching and delivery in the FNs/FAPs in conjunction with a fixed node association strategy, where the FNs communicate either with other FNs by node-to-node (N2N) communications or with the FAPs in their proximity. In both caching scenarios, we investigate the relationship between the caching probability of the file and the energy-efficient content delivery by formulating the associated energy efficiency (EE) optimization problem under caching memory constraints. Then, we derive a joint modulation mode allocation strategy and caching policy for each content caching node and conceive a joint node association and caching algorithm for maximizing the EE. Finally, we quantify both the overall EE and throughput for demonstrating that the proposed caching and transmission strategy achieves significant performance improvements. [ABSTRACT FROM AUTHOR]

By blending the concepts of non-orthogonal multiple access (NOMA) and orthogonal frequency division multiplexing, in this paper, a novel hybrid scheme is conceived for supporting diverse services in future wireless systems. Motivating to maximize energy efficiency (EE), the joint resource management of user clustering (UC) and power allocation is investigated for the downlink hybrid NOMA systems. Under two different power consumption cases, the optimal resource allocation (Opt-RA) algorithm is developed with the help of converting the original mixed integer non-linear programming (MINLP) problem to the tractable decoupled problems. For practical implementation, the heuristic resource allocation (Heur-RA) algorithm is also proposed, and it includes a low-complexity UC algorithm based on the candidate search-and-allocation approach. Our simulation results show that, both the Opt-RA and Heur-RA algorithms achieve significantly higher EE performance than other existing algorithms. Further, the results also prove that, the hybrid NOMA conceived is able to exploit the advantages of NOMA scheme, and is superior to conventional orthogonal multiple access (OMA) in terms of EE, as well as achieving higher flexibility for system configuration than NOMA. [ABSTRACT FROM AUTHOR]

This paper proposes a zone-based approach referred to as zone-based GrEEn (ZBGrEEn) algorithm, for energy-efficient spectrum sharing (SS) networks. The SS network is considered to encompass device-to-device (D2D) transmissions between a single primary transmitter (PT) and multiple primary receivers (PRs), placed in distinctive zones around the PT. Power allocation is performed optimally so that the target rate of each application demanded by the PRs are adequately met. When the PT fails to meet the target rates over ${\rm{PT}} \to {\rm{PR}}$ D2D links, it transmits cooperatively through an appropriate secondary transmitter (ST) in the SS network, which acts as an amplify-and-forward (AF) relay. The ST's basis for selection is the ${\rm{PT}} \to {\rm{ST}}$ channel state and power level at the ST. Use of game theory for solving the energy efficiency (EE) maximization problem has also been quantified. ZBGrEEn introduces zone factor for determining the transmission time for each zone in the SS network. This time determines the energy consumption at the user terminals, thereby impacting its battery lifetime. The efficiency of the proposed scheme has been validated through simulation results, with the enhancement in battery lifetime of up to 46.28% achievable for the PT. Game theory is also observed to be rewarding in battery lifetime augmentation, especially for ultradense networks (UDNs). Performance of other user terminals in the network can be similarly evaluated. [ABSTRACT FROM AUTHOR]

This paper aims at solving two classes of energy efficiency (EE) maximization problems in multiple channels wireless communication systems. First, the EE maximization problem with sum power constraint is solved based on the geometric water-filling approach; and second, the approach is extended into the EE maximization problem with additional least throughput requirement constraint. Our proposed algorithms make use of the water-filling structure of the optimal solution and provide exact and computation efficient solution to the energy-efficient power allocation problems. The proposed algorithms also have excellent scalability, which is applicable for large-scale wireless communication systems. Optimality of the proposed algorithms is strictly proved, and the proposed algorithms only require low-degree polynomial computational complexity. Numerical results are presented to demonstrate the efficiency of the proposed algorithms. To the best of our knowledge, no prior algorithms in the existing literature could provide such solutions to the EE maximization problems under the merit of exactness and the efficiency. [ABSTRACT FROM AUTHOR]

Synchronization of bio-inspired pulse-coupled oscillators is receiving increased attention due to its wide applications in sensor networks and wireless communications. However, most existing results are obtained in the absence of malicious attacks. Given the distributed and unattended nature of wireless sensor networks, it is imperative to enhance the resilience of pulse based synchronization against malicious attacks. To achieve this goal, we propose a new pulse based interaction mechanism to improve the resilience of pulse based synchronization. We rigorously characterize the condition for mounting stealthy attacks under the proposed pulse based interaction mechanism and prove analytically that synchronization of legitimate oscillators can be achieved in the presence of multiple stealthy attackers even when the initial phases are unrestricted, i.e., randomly distributed in the entire oscillation period. This is in distinct difference from most existing attack-resilient synchronization algorithms (including the seminal paper from L. Lamport and P. M. Melliar-Smith, “Synchronizing Clocks in the Presence of Faults,” J. ACM, vol. 32, no. 1, pp. 52–78, 1985), which require a priori (almost) synchronization among legitimate nodes. Numerical simulations are given to confirm the theoretical results. [ABSTRACT FROM AUTHOR]

In this paper, we study the energy efficiency (EE) optimization for simultaneous wireless information and power transfer in multiple-input-multiple-output two-way amplify-and-forward relay networks, where the energy-constrained relay harvests energy from two sources’ signals by power splitting (PS) scheme to forward the information of two sources. Our objective is to jointly design the sources and relay precoding matrices and the PS ratio to maximize the EE of the network, under the transmit power constraints at sources and relay and the minimum spectral efficiency requirement. We transform the nonconvex precoding and PS design problem into a difference of convex programming and propose an efficient iterative algorithm based on the constrained concave convex procedure to obtain a local optimum. To reduce computational complexity, we propose a generalized singular value decomposition based channel diagonalization scheme to simplify the optimization into a joint source and relay power allocation problem. The alternating optimization method is employed to solve this problem and a suboptimal solution to the EE maximization problem is obtained. Simulation results demonstrate the effectiveness of the proposed schemes. [ABSTRACT FROM AUTHOR]

In this paper, we study the energy-efficient resource allocation problem for device-to-device (D2D) communication underlaying cellular networks, which aims to maximize the minimum weighted energy efficiency of D2D links while guaranteeing minimum data rates for cellular links. We first characterize the optimal power allocation of the cellular links to transform the original resource allocation problem into the joint subchannel and power allocation problem for D2D links. We then propose three resource allocation algorithms with different complexity levels, namely, dual-based, branch-and-bound (BnB), and relaxation-based rounding (RBR) algorithms. While the dual-based algorithm solves the problem by using the dual decomposition method, the BnB and RBR algorithms tackle the problem by employing the relaxation approach. We establish the strong performance guarantees for the proposed algorithms through theoretical analysis. Extensive numerical studies demonstrate that the proposed algorithms achieve superior performance and significantly outperform a conventional algorithm. [ABSTRACT FROM PUBLISHER]

Network-wide broadcast (simply broadcast) is a frequently used operation in wireless ad hoc networks (WANETs). One promising practical approach for energy-efficient broadcast is to use localized algorithms to minimize the number of nodes involved in the propagation of the broadcast messages. In this context, the minimum forwarding set problem (MFSP) (also known as multipoint relay (MPR) problem) has received a considerable attention in the research community. Even though the general form of the problem is shown to be NP-complete, the complexity of the problem has not been known under the practical application context of ad hoc networks. In this paper, we present a polynomial time algorithm to solve the MFSP for wireless network under unit disk coverage model. We prove the existence of some geometrical properties for the problem and then propose a polynomial time algorithm to build an optimal solution based on these properties; To the best of our knowledge, our algorithm is the first polynomial time solution to the MFSP under the unit disk coverage model. We believe that the work presented in this paper will have an impact on the design and development of new algorithms for several wireless network applications including energy-efficient multicast, broadcast, and topology control protocols for WANETs and sensor networks. [ABSTRACT FROM AUTHOR]

Due to signal fading and user mobility in wireless networks, quality-of-service provisioning for wireless services has become more challenging. As a promising technique, cooperative communications make use of the broadcasting nature of the wireless medium to facilitate data transmission and, thereby, reduce energy consumption. However, in many studies on wireless cooperative diversity, it is often assumed that the number of relays or the relay distribution intensity is known a priori. In this paper, we relax this assumption and propose an algorithm to estimate the relay intensity for a backoff-based cooperative scheme, where the relays are distributed as a homogeneous Poisson point process. It is proved that the algorithm can converge to an optimal solution with the minimum estimation error. Based on the estimated relay intensity, we further investigate a distributed energy saving strategy, which selectively turns off some relays to reduce energy consumption while maintaining the required transmission success probability. The performance of the proposed cooperative scheme is analytically evaluated with respect to the collision probability. The numerical and simulation results demonstrate the high accuracy and efficiency of the intensity estimation algorithm and validate the theoretical analysis. Moreover, the proposed cooperative scheme exhibits significant energy savings and satisfactory transmission performance, which offers a good match to accommodate green communications in wireless networks. [ABSTRACT FROM PUBLISHER]

In the area of energy-efficient (EE) resource allocation, only limited work has been done on consideration of both transmitter and receiver energy consumption. In this paper, we propose a novel EE resource-allocation scheme for orthogonal frequency-division multiple-access (OFDMA) networks, where both transmitter energy consumption and receiver energy consumption are considered. In addition, different quality-of-service (QoS) requirements, including minimum-rate guarantee service and best effort service, are taken into account. The time slot, subcarrier (frequency), and power-allocation policies are jointly considered to optimize system EE. With all these considerations, the EE resource-allocation problem is formulated as a mixed combinatorial and nonconvex optimization problem, which is extremely difficult to solve. To reduce the computational complexity, we tackle this problem in three steps. First, for a given power allocation, we obtain the time–frequency resource unit (RU) allocation policy via binary quantum-behaved particle swarm optimization (BQPSO) algorithm. Second, under the assumption of known RU allocation, we transform the original optimization problem into an equivalent concave optimization problem and obtain the optimal power-allocation policy through the Lagrange dual approach. Third, an iteration algorithm is developed to obtain the joint time–frequency power–resource-allocation strategy. We validate the convergence and effectiveness of the proposed scheme by extensive simulations. [ABSTRACT FROM PUBLISHER]

This paper investigates the optimum energy efficiency (EE) and the corresponding spectral efficiency (SE) for a communication link operating over a flat-fading channel. The EE is evaluated by the total energy consumption for transmitting per message bit. Three channel cases are considered, namely static channel with channel state information available at transmitter (CSIT), fast-varying (FV) channel with channel distribution information available at transmitter (CDIT), and FV channel with CSIT. The link's circuit power is modeled as \Pcst + \CoeffPrate\Prate(R) Watt, where \Pcst>0 and \CoeffPrate≥0 are two constants and \Prate(R) is a general increasing and convex function of the transmission rate R≥0. For all the three channel cases, the tradeoff between the EE and SE is studied. It is shown that the EE improves strictly as the SE increases from 0 to the optimum SE, and then strictly degrades as the SE increases beyond the optimum SE. The impact of \CoeffPrate, \Pcst and other system parameters on the optimum EE and corresponding SE is investigated to obtain insight. Some of the important and interesting results for all the channel cases include: (1) when \CoeffPrate increases the SE corresponding to the optimum EE should keep unchanged if \Prate(R)=R, but reduced if \Prate(R) is strictly convex of R; (2) when the rate-independent circuit power \Pcst increases, the SE corresponding to the optimum EE has to be increased. A polynomial-complexity algorithm is developed with the bisection method to find the optimum SE. The insight is corroborated and the optimum EE for the three cases are compared by simulation results. [ABSTRACT FROM AUTHOR]

In this paper, we propose two cross-layer algorithms, namely, the Power-optimal Scheduling Algorithm (PSA) and the Throughput-optimal Scheduling Algorithm (TSA), to minimize energy consumption and to maximize throughput, respectively, in multihop wireless networks. Our algorithms guarantee a flow-based minimum data rate and jointly integrate congestion control, power allocation, routing, and link rate scheduling. Different from traditional algorithms that assume infinite buffers, the proposed algorithms deterministically upper bound the flow-based packet queue length and thus can be employed in multihop networks with finite buffers. In addition, the algorithms achieve a power expenditure/throughput “\epsilon-close” to the optimal value, with a tradeoff of order O(\1/\epsilon) in buffer size. The average end-to-end delay upper bound can also be derived from the finite buffer property. Finally, numerical results are presented to show the performance of the two algorithms with different system parameters. [ABSTRACT FROM PUBLISHER]

Cooperative communication (CC) offers an efficient and low-cost way to achieve spatial diversity by forming a virtual antenna array among single-antenna nodes that cooperatively share their antennas. It has been well recognized that the selection of relay nodes plays a critical role in the performance of CC. Most existing relay selection strategies focus on optimizing the outage probability or energy consumption. To fill in the vacancy of research on throughput improvement via CC, we study the relay selection problem with the objective of optimizing the throughput in this paper. For unicast, it is a P problem, and an optimal relay selection algorithm is provided with a correctness proof. For broadcast, we show the challenge of relay selection by proving it nonprobabilistic hard (NP-hard). A greedy heuristic algorithm is proposed to effectively choose a set of relay nodes that maximize the broadcast throughput. Simulation results show that the proposed algorithms can achieve high throughput under various network settings. [ABSTRACT FROM PUBLISHER]

Reducing power consumption of wireless networks has become a major goal in designing modern multimedia wireless systems. In an effort to reduce power consumption, this paper addresses the issue of scheduling real-time messages in multimedia wireless networks subject to both timing and power constraints. A power-consumption model is introduced to calculate power-consumption rates in accordance with message-transmission rates. Next, a new message-scheduling scheme called Power-aware Real-time Message (PARM) is developed to generate message-transmission schedules that minimize power consumption of multimedia wireless-network interfaces and the probability of missing deadlines for real-time messages. With a power-aware scheduling policy in place, the proposed PARM scheme is very energy-efficient. Experimental results based on a wide variety of synthetic workloads and eight real-world applications show that PARM significantly reduces energy dissipation while maintaining low missed rates. PARM reduces power consumption of data transmissions by up to 99.4% (with an average of 86.7%) for synthetic network traffic and saves energy by up to 60.0% (with an average of 34.1%) in the eight real-world applications. [ABSTRACT FROM AUTHOR]

This paper proposes a robot-deployment algorithm that overcomes unpredicted obstacles and employs full-coverage deployment with a minimal number of sensor nodes. Without the location information, node placement and spiral movement policies are proposed for the robot to deploy sensors efficiently to achieve power conservation and full coverage, while an obstacle surrounding movement policy is proposed to reduce the impacts of an obstacle upon deployment. Simulation results reveal that the proposed robot-deployment algorithm outperforms most existing robot-deployment mechanisms in power conservation and obstacle resistance and therefore achieves a better deployment performance. [ABSTRACT FROM AUTHOR]

Abstract-Connected Dominating Sets (CDSs) can serve as virtual backbones for wireless networks. A smaller virtual backbone incurs less maintenance overhead. Unfortunately, computing a minimum size CDS is NP-hard, and thus most researchers in this area concentrate on how to construct smaller CDSs. However, people neglected other important metrics of network, such as diameter and average hop distances between two communication parties. In this paper, we investigate the problem of constructing quality CDS in terms of size, diameter, and Average Backbone Path Length (ABPL). We present two centralized algorithms having constant performance ratios for its size and diameter of the constructed CDS. Especially, the size of CDS computed by the second algorithm is no more than 6.906 times of its optimal solution. Furthermore, we give its distributed version, which not only can be implemented in real situation easily but also considers energy to extend network lifetime. In our simulation, we show that in average the distributed algorithm not only generates a CDS with smaller diameter and ABPL than related work but also suppresses its size well. We also show that it is more energy efficient than others in prolonging network lifetime. [ABSTRACT FROM AUTHOR]

Communication is a primary source of energy consumption in wireless sensor networks! Due to resource constraints, the sensor nodes may not have enough energy to report every reading to the base station over a required network lifetime. This paper investigates data collection strategies in lifetime-constrained wireless sensor networks. Our objective is to maximize the accuracy of data collected by the base station over the network lifetime. Instead of sending sensor readings periodically, the relative importance of the readings is considered in data collection: the sensor nodes send data updates to the base station when the new readings differ more substantially from the previous ones. We analyze the optimal update strategy and develop adaptive update strategies for both individual and aggregate data collections. We also present two methods to cope with message losses in wireless transmission. To make full use of the energy budgets, we design an algorithm to allocate the numbers of updates allowed to be sent by the sensor nodes based on their topological relations. Experimental results using real data traces show that, compared with the periodic strategy, adaptive strategies significantly improve the accuracy of data collected by the base station. [ABSTRACT FROM AUTHOR]

Abstract-This paper addresses fault-tolerant topology control in a heterogeneous wireless sensor network consisting of several resource-rich supernodes, used for data relaying, and a large number of energy-constrained wireless sensor nodes. We introduce the κ-degree Anycast Topology Control (κ-ATC) problem, with the objective of selecting each sensor's transmission range such that each sensor is κ-vertex supernode connected and the total power consumed by sensors is minimized. Such topologies are needed for applications that support sensor data reporting, even in the event of failures of up to κ — 1 sensor nodes. We propose three solutions for the κ-ATC problem: a κ-approximation algorithm, a greedy centralized algorithm that minimizes the maximum transmission range between all sensors, and a distributed and localized algorithm that incrementally adjusts sensors' transmission range such that the κ-vertex supernode connectivity requirement is met. Extended simulation results are presented to verify our approaches. [ABSTRACT FROM AUTHOR]

This paper proposes task-scheduling algorithms designed to save energy in ad hoc networks by using a novel concept of "affinity" as the scheduling metric. This notion of affinity is used to represent the task-linking topology. For one-hop ad hoc networks, we define three types of affinity measures: node affinity, task affinity, and weighted affinity. Node affinity is defined as the weighted sum of incoming and outgoing task flows at each node, and task affinity as the sum of node affinities of source and destination nodes for each task. Based on these affinity measures, we consider three heuristic scheduling algorithms that are executable in real time: 1) affinity-first shortest task scheduling Qat; 2) task-size-first affinity-based scheduling Qta; and 3) task-size weighted-affinity scheduling Qwa. These algorithms have the advantage of making the total duration of the doze state of all the nodes in the network longer than in other conventional schemes, thereby achieving significant power saving (PS). Our simulation experiments suggest that the PS performance of Qwa is comparable to optimal scheduling (which is not implementable in practice for realistic link topologies). We also present a framework for a PS medium-access-control (MAC) protocol in which our scheduling algorithm can be deployed, and we describe how to enhance the existing 802.11 PS MAC to implement our framework. Simulation results demonstrate that our enhanced PS MAC protocol combined with affinity-based scheduling improves power efficiency and throughput significantly over other existing schemes. [ABSTRACT FROM AUTHOR]

Energy optimization is important in wireless ad hoc networks, where node battery power is usually limited. Research results show that such a network can exploit controlled node mobility to reduce communication-related energy consumption. However, node movement itself usually consumes energy. In this paper we study the energy optimization problem that accounts for energy costs associated with both communication and physical node movement. We refer to this model as in formed mobility. We first review the theoretical foundations on how to reduce total communication energy consumption, as well as increase system lifetime, by combining node movement and transmission power adaptation. Next, we describe and analyze the informed mobility optimization problem. Based on this analysis, we introduce localized algorithms and protocols for informed mobility. We propose iMobif, a flow-based informed mobility framework that collects network information for mobility decision making. We demonstrate how to use iMobif to minimize total communication energy consumption as well as to maximize system lifetime. We compare the performance of iMobif to that of systems with no mobility or only cost-unaware mobility. Simulation results show iMobif is effective in reducing energy consumption relative to such systems. [ABSTRACT FROM AUTHOR]

Energy-efficient routing is a critical problem in multihop wireless networks due to the severe power constraint of wireless nodes. Despite its importance and many research efforts toward it, a distributed routing algorithm that maximizes network lifetime is still missing. To address this problem, this paper proposes a novel utility-based nonlinear optimization formulation to the maximum lifetime routing problem. Based on this formulation, a fully distributed localized routing algorithm is further presented, which is proved to converge at the optimal point, where the network lifetime is maximized. Solid theoretical analysis and simulation results are presented to validate the proposed solution. [ABSTRACT FROM AUTHOR]

A network of sensors can be used to obtain state-based data from the area in which they are deployed. To reduce costs, the data, sent via intermediate sensors to a sink, are often aggregated (or compressed). This compression is done by a subset of the sensors called ‘aggregators.’ Inasmuch as sensors are usually equipped with small and unreplenishable energy reserves, a critical issue is to strategically deploy an appropriate number of aggregators so as to minimize the amount of energy consumed by transporting and aggregating the data. In this paper, the authors first study single-level aggregation and propose an Energy-Efficient Protocol for Aggregator Selection (EPAS) protocol. Then, they generalize it to an aggregation hierarchy and extend EPAS to Hierarchical EPAS. The optimal number of aggregators with generalized compression and power-consumption models was derived, and fully distributed algorithms for aggregator selection were presented. Simulation results show that the algorithms significantly reduce the energy consumption for data collection in wireless sensor networks. Moreover, the algorithms do not rely on particular routing protocols and are thus applicable to a broad spectrum of application environments. [ABSTRACT FROM AUTHOR]

Consider a wireless multihop network where nodes are randomly distributed in a given area following a homogeneous Poisson process. The hop count statistics, viz. the probabilities related to the number of hops between two nodes, are important for performance analysis of the multihop networks. In this paper, we provide analytical results on the probability that two nodes separated by a known euclidean distance are k hops apart in networks subject to both shadowing and small-scale fading. Some interesting results are derived which have generic significance. For example, it is shown that the locations of nodes three or more hops away provide little information in determining the relationship of a node with other nodes in the network. This observation is useful for the design of distributed routing, localization, and network security algorithms. As an illustration of the application of our results, we derive the effective energy consumption per successfully transmitted packet in end-to-end packet transmissions. We show that there exists an optimum transmission range which minimizes the effective energy consumption. The results provide useful guidelines on the design of a randomly deployed network in a more realistic radio environment. [ABSTRACT FROM AUTHOR]

In this paper, we consider the exact top-k query problem in wireless sensor networks, i.e., where one seeks to find the k highest reported values as well as the complete set of nodes that reported them. Our primary contribution in this context is EXTOK, a provably correct and topology-independent new filtering-based algorithm for processing exact top-k queries. As a secondary contribution we confirm a previous result of ours by showing that the efficiency of top-k query processing algorithms, including EXTOK, can be further improved by simply choosing a proper underlying logical tree topology. We examine EXTOK's performance with respect to a number of parameters and different logical tree topologies while using both synthetic and real data sets. Our simulation reveal that EXTOK consistently outperforms the current state-of-the-art algorithm by a very significant margin and regardless of the underlying logical tree topology. [ABSTRACT FROM AUTHOR]