Green Communications and Networking

Wireless Sensor Networks (WSNs) require an efficient intrusion detection scheme to identify malicious attackers. Traditional detection schemes are not well suited for WSNs due to their higher false detection rate. In this paper, we propose a novel intrusion detection scheme based on the energy prediction in cluster-based WSNs (EPIDS). The main contribution of EPIDS is to detect attackers by comparing the energy consumptions of sensor nodes. The sensor nodes with abnormal energy consumptions are identified as malicious attackers. Furthermore, EPIDS is designed to distinguish the types of denial of service (DoS) attack according to the energy consumption rate of the malicious nodes. The primary simulation experiments prove that EPIDS can detect and recognize malicious attacks effectively.

Due to the variety of household electric devices and different power consumption habits of consumers at present, it is a challenge to identify various electric appliances without any presetting. This paper proposed the smart appliance management system for recognizing of electric appliances in home network, which can measure the power consumption of household appliances through a current sensing device. The characteristics and categories of related electric appliances are established, and this system could search the corresponding cluster data and eliminates noise for recognition functionality and error detection mechanism of electric appliances by applying the current clustering algorithm. At the same time, this system integrates household appliance control network services to control them based on users’ power consumption plans, thus realizing a bidirectional monitoring service. In practical tests, the system reached a recognition rate of 95%, and could successfully control general household appliances in home network.

Group target usually covers a large area and is more difficult to track in wireless sensor networks. In traditional methods, much more sensors are activated and involved in tracking, which causes a heavy network burden and huge energy cost. This paper presents a Boundary Sensing Model (BSM) used to discover group target’s contour, which conserves energy by letting only a small number of sensors – BOUNDARY sensors participate in tracking. Unlike previous works, the proposed BSM is flexible by adjusting the boundary thickness thresholds. We analytically evaluate the probability of becoming a BOUNDARY sensor and the average quantity of BOUNDARY sensors, which proved to be affected by communication radius, density, and boundary thickness thresholds. Extensive simulation results confirm that our theoretical results are reasonable, and show that our proposed BSM based group target tracking method uses less number of sensors for group tracking without precision loss.

Femtocell technique has become a radical approach to improve network capacity and coverage. To efficiently reduce interference between femto BS and other BSs, low duty operation mode (LDM) is deemed as a good method to mitigate the interference. In this work, we develop a mechanism that incorporates the power saving mechanism in both femto BS (LDM mode) and MSs (sleep mode). To correspond to the current IEEE 802.16m system architecture, we build a practical system model and analyze the performance of the proposed modification. The simulation shows that with simple sleep-cycle operation, our mechanism can achieve both a high sleep ratio and an acceptable low delay without generating more control overhead than original system requirement. With the above characteristics, our mechanism provides a solid basis to create a green communication system.

Android is a widely used operating system in mobile devices, due to that it is free, open source and easy-to-use. However, the multimedia processing ability of current android is quite limited, as the original android multimedia engine OpenCore cannot deal with lots of commonly used video (audio) formats. Recently, several approaches are proposed to enhance the multimedia processing ability and Gstreamer based method is supposed to own the best performance. However, the multimedia processing ability of current extension multimedia frameworks are still not good enough, which weakens the potential application prospect. In this paper, we provide another android multimedia framework based on Gstreamer. Extensive experiments show that our Gstreamer based framework can greatly improve the multimedia processing ability in terms of efficiency, compatibility, feasibility and universality.

Computation offloading is a promising method for reducing power consumption of mobile devices by offloading computation to remote servers. For computation offloading, application partitioning is a key component. However, making a good application partitioning is challenging, as it needs to carefully consider the tradeoffs between the communication cost and computational benifits. Most of previous work makes application partitioning by using a static bandwidth to measure the communication cost and thus cannot adapt to scenarios with dynamic bandwidth. To address this problem, in this paper, we propose a Bandwidth Aware Application Partitioning Scheme (BAAP). BAAP models the bandwidth as a random variable and formulate the application partition as a 0-1 Integer Programming with Probability (IPP) problem. Then BAAP adopts Branch and Bound algorithm to solve the problem. Experimental results show that BAAP can greatly reduce energy consumption while satisfying the cost and time constraints with guaranteed confidence probabilities regardless of different network bandwidth.

In this paper we aim to demonstrate that the emerging paradigm of content-centric networking conceived for future Internet architectures can be also beneficial from the energy efficiency point of view. The reference scenario to prove this statement is a Mobile Ad hoc Network (MANET) characterized by dynamic topology and intermittent connectivity. We design CHANET, a content-centric MANET that relies on a connectionless layer built on top of legacy IEEE 802.11 networks to provide energy-efficient content-based transport functionality without relying on the TCP/IP protocol suite.

Ranging and positioning of wireless mobile devices using time-of-arrivals (TOA) method is becoming an increasingly interesting and challenging research topic. There are various TOA-based ranging algorithms and positioning systems, but most of them require either specially designed hardware or modifications to existing firmware. Using only off-the-self hardware, we present a novel software-based TOA ranging approach which accurately measures TOAs using the Real Time Application Interface (RTAI) operating system. A prototype system is implemented which provides precise measurements of round trip time (RTT) using IEEE 802.11b MAC layer ACK frames and the real-time communication mechanism provided by RTAI. Experiments show that using RTAI can achieve a ranging result with precision close to the accuracy obtained by hardware based methods.

This work reports on the benefits of using energy-efficient grooming strategies in WDM mesh networks in terms of the overall network power consumption. We examine a key enabling node architecture called tap-or-pass (TOP) and demonstrate how it can support lightpath extension and lightpath dropping. Using these grooming concepts we propose several grooming strategies. Through extensive simulation, we demonstrate that, given a network with dynamic traffic requests, the proposed grooming strategies lead to considerable energy saving and comparable request blocking, in particular when the network load is moderate.

The high power consumption of data centers confronts the providers with major challenges. However, not only the servers and the cooling consume a huge amount of energy, but also the data center network architecture makes an important contribution. In this paper, we introduce different data center architectures and compare them regarding their power consumption. The results show that there are some differences which should not be neglected and that with only minor modifications of the architecture, it is possible to save a huge amount of energy.

The purpose of this paper is to examine how a gradient-based algorithm that minimises a cost function that includes both quality of service (QoS) and power minimisation in wired networks can be used to improve energy savings with respect to shortest-path routing, as well as against a “smart” autonomic algorithm called EARP which uses adaptive reinforcement learning. Comparisons are conducted based on the same test-bed and identical network traffic. We assume that due to the need for network reliability and resilience we are not allowed to turn off routers and link drivers. We also assume that for QoS reasons (notably with regard to jitter and to avoid packet desequencing) we are not allowed to split traffic from the same flow into different paths. Under these assumptions and for the considered traffic, we observe that power consumed with the gradient-optimiser is a few percent to 10% smaller than that consumed using shortest-path routing or EARP. Since the magnitude of the savings is small, this suggests that further power savings may only be obtained if under-utilised equipment can be dynamically put to sleep or turned off.

Nodes in a cognitive radio mesh network comprised of secondary users may select from a set of available channels provided they do not interfere with primary users. This ability can improve overall network performance but introduces the question of how best to use these channels. Given a routing multipath M, we would like to choose which channels each link in M should use and a corresponding transmission schedule so as to maximize the end-to-end data flow rate (throughput) supported by the entire multipath. This problem is relevant to applications such as streaming video or data where a connection may be long lasting and require a high constant throughput as well as providing robust, high-speed communications in wireless mesh networks deployed in rural environments, where there are significant amounts of spectrum available for secondary use. Better transmission scheduling can lead to improved network efficiency and less network resource consumption, e.g. energy-use. The problem is hard to due the presence of both intra-flow and inter-flow interference. In this paper, we develop a new polynomial time constant-factor approximation algorithm for this problem. We also present an effective heuristic method for finding effective multipath routes. It has been shown by simulation results that the end-to-end throughput given by the proposed algorithms provide nearly twice the throughput of single path routes and that the schedules generated are close to optimal.

In this paper we show how cooperation can improve the overall energy efficiency of an ad hoc network. By exploiting a behavior-tracking algorithm inspired by the results of game theory and allowing traffic to be forwarded only towards cooperative nodes, we show how we can dramatically reduce power wastage at the same time maximizing goodput. Under this perspective, cooperation can definitely be seen as an incentive for all nodes, since it allows to optimize one of the most crucial parameters impacting the performance of ad hoc networks.

Energy efficiency is crucial for energy-constrained ad hoc networks. Cooperative communication can be applied to significantly reduce energy consumption. Due to the selfishness and the self-organization of nodes, the relay requests can not always be accepted by potential relay nodes with only local information, and the network overall performance can not always be improved in a distributed way. In this work, we present a distributed cooperation policy selection scheme which allows nodes to autonomously make their own cooperation decisions to achieve the global max-min fairness in terms of energy efficiency. Specifically, since the correlated equilibrium can achieve better performance by helping the noncooperative players coordinate their strategies, we model a correlated equilibrium-based cooperation policy selection game, where the individual utility function is designed from the global energy efficiency perspective. We derive the condition under which the correlated equilibrium is Pareto optimal, and propose a distributed algorithm based on the regret matching procedure that converges to the correlated equilibrium. Simulation results are provided to demonstrate the effectiveness of the proposed scheme.

The limited spectrum resources and the negative impacts of carbon dioxide emission resulted from inefficient use of wireless technologies have led to the development of green radio. Both the energy and spectral efficiencies should be considered together to meet green radio requirements. In this paper, we investigate the trade-off between energy efficiency and spectral efficiency through different approaches. Cognitive radio is a paradigm-shift technology which is used to increase both the energy and spectral efficiencies. Some efficient spectrum sensing techniques are considered in terms of energy and time consuming. Furthermore, it can be shown that the power control strategies can play a key role in avoiding interference between cognitive and primary users, and hence it can also enhance both the energy and spectral efficiencies. In addition to cognitive radio, a new infrastructure for deploying the cellular base stations which is a heterogeneous infrastructure of macro-, pico-, and femto-cells is proposed to overcome the energy and bandwidth constraints. Further details related to hardware-constraints in a green base station have also been covered.