Underwater sensing via networked platforms (i.e., underwater wireless sensor networks – UWSNs) is extremely useful in a plethora of applications such as monitoring underwater assets and surveillance against submerged threats. Maintaining reliable connectivity is of utmost importance in UWSNs, which can be achieved through k-connectivity (i.e., each sensor node maintains at least k node-disjoint paths towards the base station – BS). However, the energy cost of k-connectivity is prohibitively high, especially with large k values. As a tradeoff, it is possible to mitigate the extra energy cost of k-connectivity by employing a non-uniform k assignment strategy in a UWSN (e.g., only the most critical sensors have high k values whereas the rest of the nodes have lower k values). Non-uniform k-connectivity is a novel concept which has never been systematically investigated in the literature, to the best of our knowledge. In this study, we investigate the tradeoff between network lifetime (NetL) and reliability via non-uniform k-connectivity through the use of a novel optimization framework. Our analysis reveal that it is possible to provide strong connection reliability to critical nodes by adopting a non-uniform k-connectivity strategy without deteriorating network lifetime significantly.

Underwater wireless sensor networks (UWSNs) are utilized for a wide range of monitoring and surveillance applications. Lifetime maximization and maintenance of network reliability are among the most important considerations in the deployment of UWSNs.$k$-connectivity is a robust approach for reinforcing reliability. However, maintaining$k$disjoint paths from each sensor node to the BS, inevitably, results in extra energy dissipation, which reduces the network lifetime (NLT). Yet, there is no systematic exploration to determine the extent of lifetime reduction due to the increase in the$k$value, in the literature, to the best of our knowledge. In this study, we create an optimization framework to be able to explore the tradeoff between NLT and$k$-connectivity-based reliability in UWSNs. Through the optimal solutions of the proposed optimization model for a large set of salient parameters, we characterize the interplay between lifetime and$k$-connectivity. Our analysis reveals that the$k$value to be maintained in a UWSN can affect the NLT significantly.

Mobile sensor networks (MSNs) have emerged from the interaction between mobile robotics and wireless sensor networks. MSNs can be deployed in harsh environments, where failures in some nodes can partition MSNs into disconnected network segments or reduce the coverage area. A$k$-connected network can tolerate at least$k$-1 arbitrary node failures without losing its connectivity. In this study, we present a coverage-aware distributed$k$-connectivity maintenance (restoration) algorithm that generates minimum-cost movements of active nodes after a node failure to preserve a persistent$k$value subject to a coverage conservation criterion. The algorithm accepts a coverage conservation ratio (as a trade-off parameter between coverage and movements) and facilitates coverage with the generated movements according to this value. Extensive simulations and testbed experiments reveal that the proposed algorithm restores$k$-connectivity more efficiently than the existing restoration algorithms. Furthermore, our algorithm can be utilized to maintain$k$-connectivity without sacrificing the coverage, significantly.

We address a dynamic covering location problem of an unmanned aerial vehicle base station (UAV-BS), in which the location sequence of a single UAV-BS in a wireless communication network is determined to satisfy data demand arising from ground users. This problem is especially relevant in the context of smart grid and disaster relief. The vertical movement ability of the UAV-BS and nonconvex covering functions in wireless communication restrict utilizing classical planar covering location approaches. Therefore, we develop new formulations to this emerging problem for a finite time horizon to maximize the total coverage. In particular, we develop a mixed-integer nonlinear programming formulation that is nonconvex in nature and propose a Lagrangean decomposition algorithm (LDA) to solve this formulation. Because of the high complexity of the problem, the LDA is still unable to find good local solutions to large-scale problems. Therefore, we develop a continuum approximation (CA) model and show that CA would be a promising approach in terms of both computational time and solution accuracy. Our numerical study also shows that the CA model can be a remedy to build efficient initial solutions for exact solution algorithms. Summary of Contribution: This paper addresses a facet of mixed integer nonlinear programming formulations. Dynamic facility location problems (DFLPs) arise in a wide range of applications. However, classical DFLPs typically focus on the two-dimensional spaces. Emerging technologies in wireless communication and some other promising application areas, such as smart grids, have brought new location problems that cannot be solved with classical approaches. For practical reasons, many research attempts to solve this new problem, especially by researchers whose primary research area is not OR, have seemed far from analyzing the characteristics of the formulations. Rather, solution-oriented greedy heuristics have been proposed. This paper has two main objectives: (i) to close the gap between practical and theoretical sides of this new problem with the help of current knowledge that OR possesses to solve facility location problems and (ii) to support the findings with an exhaustive computational study to show how these findings can be applied to practice.

Connectivity maintenance is an important requirement in wireless sensor and actuator networks (WSANs) because node failures can, potentially, lead to destructive changes in the network topology, which, in turn, can create a partitioned network. Preserving k-connectivity in a WSAN is important for keeping stable connections. A k-connected network is a network that remains connected after removing any k-1 nodes. Higher k values provide more reliable connectivity and a higher level of fault tolerance. In this article, we present a distributed k-connectivity restoration approach for heterogeneous WSANs where the nodes can be static or mobile. In the proposed algorithm, each node identifies the mobile nodes in the network and its 2-hop local subgraph. After a node is incapacitated, a neighbor of the failed node calls a mobile node with minimum moving cost to the location of the failed node if the failure reduces k. A minimum cost movement path between a neighbor of the failed node and a mobile node is constructed by considering the locations of the nodes, moving costs, and obstacles. Testbed experiments and comprehensive simulations reveal that the proposed distributed algorithm is capable of restoring k-connectivity with up to 35.5% lower sent Bytes and up to 40.9% lower movement cost than the existing algorithms.

Recently, underwater acoustic sensor networks (UASNs) have been proposed to explore underwater environments for scientific, commercial, and military purposes. However, long propagation delays, high transmission losses, packet drops, and limited bandwidth in underwater propagation environments make realization of reliable and energy-efficient communication a challenging task for UASNs. To prolong the lifetime of battery-limited UASNs, two critical factors (i.e., packet size and transmission power) play vital roles. At one hand, larger packets are vulnerable to packet errors, while smaller packets are more resilient to such errors. In general, using smaller packets to avoid bit errors might be a good option. However, when small packets are used, more frames should be transmitted due to the packet fragmentation, and hence, network overhead and energy consumption increases. On the other hand, increasing transmission power reduces frame errors, but this would result in unnecessary energy consumption in the network. To this end, the packet size and transmission power should be jointly considered to improve the network lifetime. In this study, an optimization framework via an integer linear programming (ILP) has been proposed to maximize the network lifetime by joint optimization of the transmission power and packet size. In addition, a realistic link-layer energy consumption model is designed by employing the physical layer characteristics of UASNs. Extensive numerical analysis through the optimization model has been also performed to investigate the tradeoffs caused by the transmission power and packet size quantitatively.

A critical node (cut vertex or articulation point) in wireless sensor networks, is a node which its failure breaks the connectivity of the network. Therefore, it is crucial that critical nodes be detected and treated with caution. This paper provides two localized distributed algorithms for determining the states of nodes (critical or noncritical). The first proposed algorithm identifies most of the critical and noncritical dominator nodes from two-hop local subgraph and connected dominating set (CDS) information that limits the computational complexity to O(Δ2) and bit complexity to O(clog2n) where Δ is the maximum node degree, c is the critical node count, and n is the node count. The testbed experiments and simulation results show that this algorithm detects up to 93% of critical nodes and achieves up to 91% of state determination with low energy consumption. The second proposed algorithm, which is based on the first one, finds the states of all nodes by running a limited distributed depth-first search algorithm in unrecognized parts of the network without traversing the whole network. Comprehensive testbed experiments and simulation results reveal that, in the presence of a CDS, this algorithm finds all critical nodes with lower energy consumption than all existing algorithms.

A key enabler for the smart grid is the fine-grained monitoring of power utilization. Although such a mechanism is helpful in the optimization of the whole electricity generation, distribution, and consumption cycle, it also creates opportunities for the potential adversaries in deducing the activities and habits of the subscribers. In fact, by utilizing the standard and readily available tools of nonintrusive load monitoring (NILM) techniques on the metered electricity data, many details of customers' personal lives can be easily discovered. Therefore, prevention of such adversarial exploitations is of utmost importance for privacy protection. One strong privacy preservation approach is the modification of the metered data through the use of on-site storage units in conjunction with renewable energy resources. In this study, we introduce a novel mathematical programming framework to model eight privacy-enhanced power-scheduling strategies inspired and elicited from the literature. We employ all the relevant techniques for the modification of the actual electricity utilization (i.e., on-site battery, renewable energy resources, and appliance load moderation). Our evaluation framework is the first in the literature, to the best of our knowledge, for a comprehensive and fair comparison of the load-shaping techniques for privacy preservation. In addition to the privacy concerns, we consider monetary cost and disutility of the users in our objective functions. Evaluation results show that privacy preservation strategies in the literature differ significantly in terms of privacy, cost, and disutility metrics.

As many countries embark on a major transitioning to the Smart Grid (SG), realizing the benefits of the new paradigm depends on generation, collection, and usage of unprecedented amount of data. With such proliferated data processing, there are legitimate concerns that call for sound privacy measures to ensure proper safekeeping. A significant portion of the potential benefits of the SG initiative, thus, relies on devising convincing mechanisms to strengthen the privacy. As a new distribution subsystem, microgrids are expected to play a crucial role in the SG. In this paper, we develop a privacy-aware microgrid power scheduling formulation with renewable sources and energy storage where five different classes of appliances are prioritized by smart meters. Our analysis shows that there is a tradeoff between maximizing the power usage and privacy levels. Hence, it is not possible to find a solution that maximizes both objectives simultaneously. However, it is possible to achieve significantly higher levels of privacy preservation with moderate sacrifice from the power usage, especially when the number of users is high.

Routing, subchannel scheduling, and power allocation are generally treated as separate problems in relay-enhanced OFDMA-based cellular networks. They are mostly modeled using non-linear constraints to maximize either sum rate or minimum rate. Although separation of problems simplifies modeling, it can lead to suboptimal solutions which can degrades network efficiency (i.e., low sum rate or low minimum rate). Also, models that include non-linear constraints generally belong to the NP-hard class. In this study, we jointly optimize routing, subchannel scheduling, and power allocation in relay-enhanced OFDMA-based cellular networks through a novel Linear Programming (LP) framework employing discrete power levels. Our framework is comprised of LP models for the following problems: Sum Rate Maximization (SRM), Max-Min Fairness (MMF), and Joint Sum Rate Maximization and Max-Min Fairness (JSRM3F). We investigate the trade-offs in sum rate maximization and max-min fairness in terms of achievable maximum data rates and subchannel sharing by numerical evaluations of the LP models. We show that maximum data rates obtained with discrete power allocation are near-optimal even with a few discrete power levels. We provide upper bounds for joint maximization of sum rate and minimum rate. Furthermore, the results of this study reveal that fairness has a significant impact on subchannel sharing.

Optimization of flows to maximize Wireless Sensor Network (WSN) lifetime is a problem already investigated in various aspects. However, most studies ignored the effects of finite bandwidth. As source data rate of sensor nodes increases, flow patterns that balance energy dissipation optimally might need more bandwidth than available. As a result, ignoring bandwidth limitations may lead to infeasible solutions. In this study, we make a comprehensive evaluation of the impacts of finite bandwidth by building a linear programming framework. The objective is the minimization of the energy expenditure in the maximum energy-dissipating node to achieve the maximum lifetime under bandwidth constraints. Our analysis reveals that energy consumption values may stay constant until a threshold data rate is reached. But, after the threshold the energy values increase because suboptimal paths are used due to bandwidth constraints. The bandwidth for optimal energy dissipation is limited approximately by twice the minimum bandwidth requirement.

Transmission power control has paramount importance in the design of energy-efficient wireless sensor networks (WSNs). In this paper, we systematically explore the effects of various transmission power control strategies on WSN lifetime with an emphasis on discretization of power levels and strategies for transmission power assignment. We investigate the effects of the granularity of power levels on energy dissipation characteristics through a linear programming framework by modifying a well known and heavily utilized continuous transmission power model (HCB model). We also investigate various transmission power assignment strategies by using two sets of experimental data on Mica motes. A novel family of mathematical programming models are developed to analyze the performance of these strategies. Bandwidth requirements of the proposed transmission power assignment strategies are also investigated. Numerical analysis of our models are performed to characterize the effects of various design parameters and to comparethe relative performance of transmission power assignment strategies. Our results show that the granularity of discrete energy consumption has a profound impact on WSN lifetime, furthermore, more fine-grained control of transmission power (i.e., link level control) can extend network lifetime up to 20% in comparison to optimally-assigned network-level single transmission power.

It is well-known that in wireless sensor networks using minimum-energy paths to transfer data from sensor nodes to base station is not an energy-balancing option and not the optimal solution if lifetime, defined as the duration till the first node in the network exhausts all its energy, is of concern. However, the net effect of minimum-energy routing on network lifetime has not been studied in detail before. In this study, we present comparative analysis using both simulations and linear programming models to investigate this issue with respect to various system parameters such as energy model, network area and number of nodes. Our results show that network lifetime achieved with minimum-energy routing could be as low as 19.3% of the maximum achievable lifetime depending on the values of other system parameters.

The occurrence of unidirectional links in wireless sensor networks (WSNs) is an inherent feature of wireless communication. Transceiver characteristics, asymmetric interference, and many other properties of the electromagnetic propagation environment result in link unidirectionality, however, transmission power heterogeneity is the dominant factor that creates unidirectional links. Most of the data transfer mechanisms designed for wireless networks work only on bidirectional links, yet, there are some mechanisms capable of utilizing unidirectional links. Employment of a multi-hop reverse path for acknowledgement delivery is the key concept and hop length of the reverse path is an important design criterion in such mechanisms. If the maximum reverse path length is allowed to take large values then the number of usable unidirectional links increases. Increasing the number of available links leads to better energy balancing and longer network lifetime. But is it necessary to keep the reverse path length large to achieve the maximum network lifetime possible? In this study, we investigate the effects of reverse path length in WSNs with unidirectional links induced by transmission power heterogeneity on network lifetime through a novel mixed integer programming framework. Our results show that reverse path length has significant impact on WSN lifetime.

Maximization of network lifetime is one of the most important design goals in Wireless Sensor Networks (WSNs). In WSNs with static base stations, sensor nodes close to the base station dissipate most of their energies for relaying other sensor nodes' data. Although cooperation among the sensor nodes results in longer network lifetimes in comparison to greedy approaches, there is an inherent limit on the achievable network lifetime due to the limited energy of the sensor nodes in close proximity of the base station acting as relays. Base station mobility is proposed as a remedy for the WSN hot spot problem. As the base station relocates, the burden of relaying the data coming from all sensor nodes can be shared by a larger set of nodes. To take advantage of base station mobility to maximize the network lifetime, determining the optimal mobility pattern is of utmost importance. In this study, we investigate the impact of using three base station mobility patterns which are random mobility, grid mobility, and spiral mobility. To avoid the shadowing effects of specific protocols or algorithms we build a novel Mixed Integer Programming (MIP) framework which enables us to explore the design space under optimal operating conditions.

In this paper, we present Multicasting through Time Reservation using Adaptive Control for Energy efficiency (MC--TRACE), an energy-efficient real-time data multicasting architecture for mobile ad hoc networks. MC-TRACE is a cross-layer design, where the medium access control layer functionality and the network layer functionality are performed by a single integrated layer. The basic design philosophy behind the multicast routing part of the architecture is to establish and maintain an active multicast tree surrounded by a passive mesh within a mobile ad hoc network. Thus, the MC-TRACE multicast backbone is a condensed passive mesh woven around a highly pruned tree. Although tree- and mesh-based multicasting techniques have been used separately in existing multicasting architectures, the novelty in this study is the integration and reengineering of the tree and mesh structures to make them highly energy efficient and robust for real-time data multicasting in mobile ad hoc networks. Energy efficiency is achieved by enabling the nodes to switch to sleep mode frequently and by eliminating most of the redundant data receptions. We evaluated the performance of MC-TRACE through ns - 2 simulations and compared it with ODMRP. Our results show that MC-TRACE provides superior energy efficiency while producing competitive QoS performance and bandwidth efficiency.

As wireless sensor networks utilize battery-operated nodes, energy efficiency is of paramount importance at all levels of system design. In order to save energy in the transfer of data from the sensor nodes to one or more sinks, the data may be routed through other nodes rather than transmitting it directly to the sink(s). In this article, we investigate the problem of energy-efficient transmission of data over a noisy channel, focusing on the setting of physical-layer parameters. We derive a metric called the energy per successfully received bit, which specifies the expected energy required to transmit a bit successfully over a particular distance given a channel noise model. By minimizing this metric, we can find, for different modulation schemes, the energy-optimal relay distance and the optimal transmit energy as a function of channel noise level and path loss exponent. These results enable network designers to select the hop distance, transmit power, and/or modulation scheme that maximize network lifetime.

In this paper, we present NB-TRACE, which is an energy-efficient network-wide voice broadcasting architecture for mobile ad hoc networks. In the NB-TRACE architecture, the network is organized into overlapping clusters through a distributed algorithm, where the clusterheads create a nonconnected dominating set. Channel access is regulated through a distributed TDMA scheme maintained by the clusterheads. The first group of packets of a broadcast session is broadcast through flooding, where each data rebroadcast is preceded by an acknowledgment to the upstream node. Nodes that do not get an acknowledgment for a predetermined time, except the clusterheads, cease to rebroadcast, which prunes the redundant retransmissions. The connected dominating set formed through this basic algorithm is broken in time due to node mobility. The network responds to the broken links through multiple mechanisms to ensure the maintenance of the connected dominating set. We compare NB-TRACE with four network layer broadcast routing algorithms (flooding, gossiping, counter-based broadcasting, and distance-based broadcasting) and three medium access control protocols (IEEE 802.11, SMAC, and MH-TRACE) through extensive ns-2 simulations. Our results show that NB-TRACE outperforms other network/MAC layer combinations in minimizing energy dissipation and optimizing spatial reuse, while producing competitive QoS performance

We present network-wide broadcasting through time reservation using adaptive control for energy efficiency (NB-TRACE), which is an energy-efficient network-wide voice broadcasting architecture for mobile ad hoc networks. In the NB-TRACE architecture, the network is organized into overlapping clusters, where the clusterheads create a non-connected dominating set. Channel access is regulated through a locally maintained distributed TDMA scheme. The first group of packets of a broadcast session is broadcast through blind flooding. Each data rebroadcast includes an implicit acknowledgement to the upstream node. Nodes that do not get acknowledgement for a predetermined time, except the clusterheads, cease to rebroadcast, which prunes redundant retransmissions. The distributed connected dominating set formed through this basic algorithm is broken in time due to node mobility. The network responds to the broken links through passive and active clusterhead data transmission monitoring to ensure the maintenance of the connected dominating set. We compare NB-TRACE with flooding and gossiping using MH-TRACE, IEEE 802.11, and SMAC medium access control protocols through ns-2 simulations. Our results show that NB-TRACE outperforms other network/MAC layer combinations in terms of energy efficiency, packet delivery ratio, jitter, and number of rebroadcasts.

In this paper, we investigate the effects of channel noise on the performance of coordinated and non-coordinated MAC protocols. Comparative evaluations of these protocols under a perfect channel assumption have shown that coordinated MAC protocols, which regulate channel access locally, outperform non-coordinated channel access schemes in terms of energy efficiency and throughput. However, coordinated MAC protocols are more vulnerable than non-coordinated MAC protocols to channel noise due to their dependence on the robustness of the control traffic. In order to observe the degradation in performance of a coordinated MAC protocol (MH-TRACE), we investigate the impact of losing control packets. Furthermore, the performance in terms of throughput, delay, and energy efficiency of both coordinated (MH-TRACE) and non-coordinated (IEEE 802.11) MAC protocols is explored using a general error model that takes into account the length of the packets. Our results show that despite its higher level of vulnerability, the coordinated MAC protocol's performance is superior to the performance of the non-coordinated MAC protocol even when error rates are high.

In this paper, we propose multihop time reservation using adaptive control for energy efficiency (MH-TRACE), which is a medium access control (MAC) protocol that combines advantageous features of fully centralized and fully distributed networks for energy-efficient real-time packet broadcasting in a multihop radio network. We introduce a novel clustering algorithm that dynamically organizes the network into two-hop clusters. MH-TRACE clusters are just for coordinating channel access and minimizing interference; thus, ordinary nodes are not static members of any cluster. Time is organized into cyclic superframes, which consist of several time frames, to support reservation-based periodic channel access for real-time traffic. Each clusterhead chooses the frame with least interference based on its own measurements for the operation of its cluster. Energy dissipation for receiving unwanted or collided data packets or for waiting in idle mode is avoided through the use of information summarization packets sent prior to the data transmissions by the source nodes. Through the use of transmission schedules within each cluster, managed by the clusterheads, intracluster data collisions are completely eliminated and intercluster collisions are minimized. We investigated MH-TRACE through extensive simulations and theoretical analysis. Our results show that MH-TRACE outperforms existing distributed MAC protocols like IEEE 802.11 and sensor MAC, in terms of energy efficiency and throughput, approaching the theoretical maximum throughput and theoretical minimum energy dissipation.

Time reservation using adaptive control for energy efficiency (TRACE) is a time frame based media access control (MAC) protocol designed primarily for energy-efficient reliable real-time voice packet broadcasting in a peer-to-peer, single-hop infrastructureless radio network. Such networks have many application areas for various scenarios that obey a strongly connected group mobility model, such as interactive group trips, small military or security units, and mobile groups of hearing impaired people. TRACE is a centralized MAC protocol that separates contention and data transmission, providing high throughput, bounded delay, and stability under a wide range of data traffic. Furthermore, TRACE uses dynamic scheduling of data transmissions and data summarization prior to data transmission to achieve energy efficiency, which is crucial for battery operated lightweight radios. In addition, energy dissipation is evenly distributed among the nodes by switching network controllers when the energy from the current controller is lower than other nodes in the network, and reliability is achieved through automatic controller backup features. TRACE can support multiple levels of quality-of-service, and minimum bandwidth and maximum delay for voice packets are guaranteed to be within certain bounds. In this paper, we describe TRACE in detail and evaluate its performance through computer simulations and theoretical analysis.