Efficient wireless multimedia multicast in multi-rate multi-channel mesh networks.

Devices in wireless mesh networks can operate on multiple channels (MC) and automatically adjust their transmission rates for the occupied channels. This paper shows how to improve performance-guaranteed multicasting transmission coverage for wireless multihop mesh networks by exploring the transmission opportunity offered by multiple rates (MR) and MC. Based on the characteristics of transmissions with different rates, we propose and analyze parallel low-rate transmissions and alternative rate transmissions (ART) to explore the advantages of MRMC in improving the performance and coverage tradeoff under the constraint of limited channel resources. We then apply these new transmission schemes to improve the WMN multicast experience. Combined with the strategy of reliable interference-controlled connections, a novel MRMC multicast algorithm (LC-MRMC) is designed to make efficient use of channel and rate resources to greatly extend wireless multicast coverage with high throughput and short delay performance. Our NS2 simulation results prove that ART and LC-MRMC achieve improved wireless transmission quality across much larger areas as compared to other related studies

Wireless information and energy transfer in nonregenerative OFDM AF relay systems.

Energy harvesting (EH) is a promising strategy to prolong the operation of energy-constrained wireless systems. Simultaneous wireless information and energy transfer (SWIET) is a potential EH technique which has recently drawn significant attention. By employing SWIET at relay nodes in wireless relay systems, the relay nodes can harvest energy and receive information from their source nodes simultaneously as radio signals can carry energy as well as information at the same time, which solves the energy scarcity problem for wireless relay nodes. In this paper, we study SWIET for nonregenerative orthogonal-frequency-division multiplexing (OFDM) amplify-and-forward systems in order to maximize the end-to-end achievable rate by optimizing resource allocation. Firstly, we propose an optimal energy-transfer power allocation policy which utilizes the diversity provided by OFDM modulation. We then validate that the ordered-signal-to-noise ratio (SNR) subcarrier pairing (SP) is the optimal SP scheme. After that, we investigate the information-transfer power allocation (IPA) and EH time optimization problem which is formulated as a non-convex optimization problem. By making the approximation at high SNR regime, we convert this non-convex optimization problem into a quasi-convex programming problem, where an algorithm is derived to jointly optimize the IPA and EH time. By analytical analysis, we validate that the proposed resource allocation scheme has much lower computational complexity than peer studies in the literature. Finally, simulation results verify the optimality of our proposed resource allocation scheme

Optimal resource allocation in wireless-powered OFDM relay networks.

This paper studies resource allocation in wireless-powered orthogonal-frequency-division multiplexing (OFDM) amplify-and-forward (AF) or decode-and-forward (DF) relay networks with time-switching (TS) based relaying. Our objective is to maximize end-to-end achievable rates by optimizing TS ratios of energy transfer (ET) and information transmission (IT), power allocation (PA) over all subcarriers for ET and IT as well as subcarrier pairing (SP) for IT. The formulated resource allocation problem is a mixed integer programming (MIP) problem, which is prohibitive and fundamentally difficult to solve. To simplify the MIP problem, we firstly provide an optimal ET policy and an optimal SP scheme, and then obtain a nonlinear programming problem to optimize TS ratios and PA for IT. Nevertheless, the obtained nonlinear programming problem is non-convex and still hard to tackle directly. To make it tractable, we transform the non-convex problem into a fractional programming problem, which is further converted into an equivalent optimization problem in subtractive form. By deriving the optimal solution to the equivalent optimization problem, we propose a globally optimal resource allocation scheme which bears much lower complexity as compared to the suboptimal resource allocation in the literature. Finally, our simulation results verify the optimality of our proposed resource allocation scheme and show that it outperforms the existing scheme in literature

Performance Evaluation of The Split Transmission in Multihop Wireless Networks

Multimedia applications in multihop wireless networks have great market potential. Multiple channels and multiple radios are commonly used for exploring multimedia transmissions in multihop wireless networks. Split transmission allows multiple channels attached to different radios simultaneously to be used, and so to achieve a fundamentally improved transmission capacity. The goal of this paper is to present a theoretical background to justify the improved performance of split transmission. We believe that this is the first attempt to consider split transmission in theory

Adaptive split transmission for video streams in wireless mesh networks

Wireless mesh networks hold great promise in the wireless transmission of video flows, particularly if the problem of providing sufficient network capacity can be addressed. For this reason, schemes which help to address this difficulty in capacity-limited wireless networks are of great interest. This paper presents a novel and simple algorithm, adaptive split transmission algorithm, for achieving real-time, and quality-guaranteed video transmission in wireless mesh networks. The algorithm utilizes the unused capacities of multiple channels rather than trying to transmit the flow over just one overloaded channel. The flow is efficiently split into several sub-flows in a capacity-aware manner, each sub-flow then being transmitted through different channels in parallel. The adaptive split transmission algorithm controls flows dynamically in response to changes in the states of the available channels, thereby avoiding the overloading of any one channel. We evaluate the algorithm through simulations. The results show that the adaptive split transmission algorithm achieves synchronized, quality-guaranteed, and real-time wireless video transmission. The proposed algorithm can be used for interactive real-time wireless video applications without changing current wireless hardware, MAC protocols and upper-layer protocols

RAODV: An Entropy-based Congestion Control for the AODV Routing Protocol

In networks, congestion causes packet loss and transmission delays. This paper presents a modified AODV routing protocol to detect and relieve congestion: R-AODV. We add an early congestion detection and avoidance mechanism to the route discovery process to achieve this purpose. In most previous congestion detection schemes, the affected node itself detects whether it is congested or not. The early detection and avoidance algorithm in this paper employs entropy estimation to determine the congestion status of a node’s neighbours and establish a less congested route by avoiding the congested nodes. Moreover, RAODV presents a multipath routing mechanism to support a backup route for the sender nodes. Finally, R-AODV provides a local replacement mechanism for route maintenance to improve the network performance

Worst-case delay control in multigroup overlay networks

This paper proposes a novel and simple adaptive control algorithm for the effective delay control and resource utilization of end host multicast (EMcast) when the traffic load becomes heavy in a multigroup network with real-time flows constrained by (sigma, rho) regulators. The control algorithm is implemented at the overlay networks and provides more regulations through a novel (sigma, rho, lambda) regulator at each group end host who suffers from heavy input traffic. To our knowledge, it is the first work to incorporate traffic regulators into the end host multicast to control heavy traffic output. Our further contributions include a theoretical analysis and a set of results. We prove the existence and calculate the value of the rate threshold rho* such that for a given set of K groups, when the average rate of traffic entering the group end hosts rho macr > rho*, the ratio of the worst-case multicast delay bound of the proposed (sigma, rho, lambda) regulator over the traditional (sigma, rho) regulator is O(1/Kn) for any integer n. We also prove the efficiency of the novel algorithm and regulator in decreasing worst-case delays by conducting computer simulations

A lightweight Intrusion Detection for Internet of Things-based smart buildings

The integration of Internet of Things (IoT) devices into commercial or industrial buildings to create smart environments, such as Smart Buildings (SBs), has enabled real-time data collection and processing to effectively manage building operations. Due to poor security design and implementation in IoT devices, SB networks face an array of security challenges and threats (e.g., botnet malware) that leverage IoT devices to conduct Distributed Denial of Service (DDoS) attacks on the Internet infrastructure. Machine Learning (ML)-based traffic classification systems aim to automatically detect such attacks by effectively differentiating attacks from benign traffic patterns in IoT networks. However, there is an inherent accuracy-efficiency tradeoff in network traffic classification tasks. To balance this tradeoff, we develop an accurate yet lightweight device-specific traffic classification model. This model classifies SB traffic flows into four types of coarse-grained flows, based on the locations of traffic sources and the directions of traffic transmissions. Through these four types of coarse-grained flows, the model can extract simple yet effective flow rate features to conduct learning and predictions. Our experiments find the model to achieve an overall accuracy of 96%, with only 32 features to be learned by the ML model