Kaoru Ota

Energy Efficiency and Spectral Efficiency Tradeoff in Device-to-Device (D2D) Communications

In this letter, we investigate the tradeoff between energy efficiency (EE) and spectral efficiency (SE) in device-to-device communications underlaying cellular networks with uplink channel reuse. The resource allocation problem is modeled as a noncooperative game, in which each user equipment is self-interested and wants to maximize its own EE. Given the SE requirement and maximum transmission power constraints, a distributed energy-efficient resource allocation algorithm is proposed by exploiting the properties of the nonlinear fractional programming. The relationships between the EE and SE tradeoff of the proposed algorithm and system parameters are analyzed and verified through computer simulations.

Joint Optimization of Lifetime and Transport Delay under Reliability Constraint Wireless Sensor Networks

This paper first presents an analysis strategy to meet requirements of a sensing application through trade-offs between the energy consumption (lifetime) and source-to-sink transport delay under reliability constraint wireless sensor networks. A novel data gathering protocol named Broadcasting Combined with Multi-NACK/ACK (BCMN/A) protocol is proposed based on the analysis strategy. The BCMN/A protocol achieves energy and delay efficiency during the data gathering process both in intra-cluster and inter-cluster. In intra-cluster, after each round of TDMA collection, a cluster head broadcasts NACK to indicate nodes which fail to send data in order to prevent nodes that successfully send data from retransmission. The energy for data gathering in intra-cluster is conserved and transport delay is decreased with multi-NACK mechanism. Meanwhile in inter-clusters, multi-ACK is returned whenever a sensor node sends any data packet. Although the number of ACKs to be sent is increased, the number of data packets to be retransmitted is significantly decreased so that consequently it reduces the node energy consumption. The BCMN/A protocol is evaluated by theoretical analysis as well as extensive simulations and these results demonstrate that our proposed protocol jointly optimizes the network lifetime and transport delay under network reliability constraint.

ActiveTrust: Secure and Trustable Routing in Wireless Sensor Networks

Wireless sensor networks (WSNs) are increasingly being deployed in security-critical applications. Because of their inherent resource-constrained characteristics, they are prone to various security attacks, and a black hole attack is a type of attack that seriously affects data collection. To conquer that challenge, an active detection-based security and trust routing scheme named ActiveTrust is proposed for WSNs. The most important innovation of ActiveTrust is that it avoids black holes through the active creation of a number of detection routes to quickly detect and obtain nodal trust and thus improve the data route security. More importantly, the generation and the distribution of detection routes are given in the ActiveTrust scheme, which can fully use the energy in non-hotspots to create as many detection routes as needed to achieve the desired security and energy efficiency. Both comprehensive theoretical analysis and experimental results indicate that the performance of the ActiveTrust scheme is better than that of the previous studies. ActiveTrust can significantly improve the data route success probability and ability against black hole attacks and can optimize network lifetime.

RMER: Reliable and Energy-Efficient Data Collection for Large-Scale Wireless Sensor Networks

We propose a novel event data collection approach named reliability and multipath encounter routing (RMER) for meeting reliability and energy efficiency requirements. The contributions of the RMER approach are as follows. 1) Fewer monitor nodes are selected in hotspot areas that are close to the Sink, and more monitor nodes are selected in nonhotspot areas, which can lead to increased network lifetime and event detection reliability. 2) The RMER approach sends data to the Sink by converging multipath routes of event monitoring nodes into a one-path route to aggregate data. Thus, energy consumption can be greatly reduced, thereby enabling further increased network lifetime. Both theoretical and experimental simulation results show that RMER applied to event detection outperforms other solutions. Our results clearly indicate that RMER increases energy efficiency by 51% and network lifetime by 23% over other solutions while guaranteeing event detection reliability.

UAV-assisted data gathering in wireless sensor networks

An unmanned aerial vehicle (UAV) is a promising carriage for data gathering in wireless sensor networks since it has sufficient as well as efficient resources both in terms of time and energy due to its direct communication between the UAV and sensor nodes. On the other hand, to realize the data gathering system with UAV in wireless sensor networks, there are still some challenging issues remain such that the highly affected problem by the speed of UAVs and network density, also the heavy conflicts if a lot of sensor nodes concurrently send its own data to the UAV. To solve those problems, we propose a new data gathering algorithm, leveraging both the UAV and mobile agents (MAs) to autonomously collect and process data in wireless sensor networks. Specifically, the UAV dispatches MAs to the network and every MA is responsible for collecting and processing the data from sensor nodes in an area of the network by traveling around that area. The UAV gets desired information via MAs with aggregated sensory data. In this paper, we design a itinerary of MA migration with considering the network density. Simulation results demonstrate that our proposed method is time- and energy-efficient for any density of the network.

Energy-Efficient Resource Allocation for D2D Communications Underlaying Cloud-RAN-Based LTE-A Networks

Device-to-device (D2D) communication is a key enabler to facilitate the realization of the Internet of Things (IoT). In this paper, we study the deployment of D2D communications as an underlay to long-term evolution-advanced (LTE-A) networks based on novel architectures such as cloud radio access network (C-RAN). The challenge is that both energy efficiency (EE) and quality of service (QoS) are severely degraded by the strong intracell and intercell interference due to dense deployment and spectrum reuse. To tackle this problem, we propose an energy-efficient resource allocation algorithm through joint channel selection and power allocation design. The proposed algorithm has a hybrid structure that exploits the hybrid architecture of C-RAN: distributed remote radio heads (RRHs) and centralized baseband unit (BBU) pool. The distributed resource allocation problem is modeled as a noncooperative game, and each player optimizes its EE individually with the aid of distributed RRHs. We transform the nonconvex optimization problem into a convex one by applying constraint relaxation and nonlinear fractional programming. We propose a centralized interference mitigation algorithm to improve the QoS performance. The centralized algorithm consists of an interference cancellation technique and a transmission power constraint optimization technique, both of which are carried out in the centralized BBU pool. The achievable performance of the proposed algorithm is analyzed through simulations, and the implementation issues and complexity analysis are discussed in detail.

Achieving Source Location Privacy and Network Lifetime Maximization Through Tree-Based Diversionary Routing in Wireless Sensor Networks

Wireless sensor networks (WSNs) have been proliferating due to their wide applications in both military and commercial use. However, one critical challenge to WSNs implementation is source location privacy. In this paper, we propose a novel tree-based diversionary routing scheme for preserving source location privacy using hide and seek strategy to create diversionary or decoy routes along the path to the sink from the real source, where the end of each diversionary route is a decoy (fake source node), which periodically emits fake events. Meanwhile, the proposed scheme is able to maximize the network lifetime of WSNs. The main idea is that the lifetime of WSNs depends on the nodes with high energy consumption or hotspot, and then the proposed scheme minimizes energy consumption in hotspot and creates redundancy diversionary routes in nonhotspot regions with abundant energy. Hence, it achieves not only privacy preservation, but also network lifetime maximization. Furthermore, we systematically analyze the energy consumption in WSNs, and provide guidance on the number of diversionary routes, which can be created in different regions away from the sink. In addition, we identify a novel attack against phantom routing, which is widely used for source location privacy preservation, namely, direction-oriented attack. We also perform a comprehensive analysis on how the direction-oriented attack can be defeated by the proposed scheme. Theoretical and experimental results show that our scheme is very effective to improve the privacy protection while maximizing the network lifetime.

LSCD: A Low-Storage Clone Detection Protocol for Cyber-Physical Systems

Cyber-physical systems (CPSs) have recently become an important research field not only because of their important and varied application scenarios, including transportation systems, smart homes, surveillance systems, and wearable devices but also because the fundamental infrastructure has yet to be well addressed. Wireless sensor networks (WSNs), as a type of supporting infrastructure, play an irreplaceable role in CPS design. Specifically, secure communication in WSNs is vital because information transferred in the networks can be easily stolen or replaced. Therefore, this paper presents a novel distributed low-storage clone detection protocol (LSCD) for WSNs. We first design a detection route along the perpendicular direction of a witness path with witness nodes deployed in a ring path. This ensures that the detection route must encounter the witness path because the distance between any two detection routes must be smaller than the witness path length. In the LSCD protocol, clone detection is processed in a nonhotspot region where a large amount of energy remains, which can improve energy efficiency as well as network lifetime. Extensive simulations demonstrate that the lifetime, storage requirements, and detection probability of our protocol are substantially improved over competing solutions from the literature.

Game-theoretic approach to energy-efficient resource allocation in device-to-device underlay communications

Despite the numerous benefits brought by device-to-device (D2D) communications, the introduction of D2D into cellular networks poses many new challenges in the resource allocation design because of the co-channel interference caused by spectrum reuse and limited battery life of user equipments (UEs). Most of the previous studies mainly focus on how to maximise the spectral efficiency and ignore the energy consumption of UEs. In this study, the authors study how to maximise each UEs Energy Efficiency (EE) in an interference-limited environment subject to its specific quality of service and maximum transmission power constraints. The authors model the resource allocation problem as a non-cooperative game, in which each player is self-interested and wants to maximise its own EE. A distributed interference-aware energy-efficient resource allocation algorithm is proposed by exploiting the properties of the nonlinear fractional programming. The authors prove that the optimal solution obtained by the proposed algorithm is the Nash equilibrium of the non-cooperative game. The authors also analyse the tradeoff between EE and SE and derive closed-form expressions for EE and SE gaps.

Service Pricing Decision in Cyber-Physical Systems: Insights from Game Theory

In cyber-physical systems (CPS), service organizers (SOs) aim to collect service from service entities at lower price and provide better combined services to users. However, each entity receives payoffs when providing services, which leads to competition between SOs and service entities or within internal service entities. In this paper, we first formulate the price competition model of SOs where the SOs dynamically increase and decrease their service prices periodically according to the number of collected services from entities. A game based services price decision (GSPD) model which depicts the process of price decisions is proposed in this paper. In the GSPD model, entities game with other entities under the rule of “survival of the fittest” and calculate payoffs according to their own payoff-matrix, which leads to a Pareto-optimal equilibrium point. Numerous experiments demonstrate that the GSPD model can explain the price dynamics in the real world, and also can help decision makers a lot under various scenarios.