Energy-Efficient Multi-Key Security Scheme for Wireless Sensor Network

This paper proposes multi-key encryption scheme and engine architecture (MKE) that increases security and optimizes energy efficiency of sensor networks, while minimizing modifications to existing implementations. The scheme improves security of AES against correlation power analysis (CPA) attack by employing MKE engine, breaking the correlation between power consumption and the used key. Other schemes utilize complex hardware designs, for example by using the inhomogeneous s-boxes that reduce energy efficiency of the engine. In contrast, the proposed hardware engine uses a randomly sequence of few keys to encode subsequent blocks of a messages. Additionally, the scheme improves security of AES against brute-force attacks for a given key size by utilizing multiple keys to encrypt subsequent blocks of a message. In contrast, a typical security upgrade would require a larger key size and encryption engine, which would increase cost and energy consumption of the devices. Both analytical and simulation results are presented in this paper

Dynamic Programming-Based Energy-efficient Rate Adaptation for Wireless Ad Hoc Networks

Resource constraints require that ad hoc wireless networks are energy efficient during transmission and rate adaptation. In this paper we propose a novel cross-layer energy-efficient rate adaptation scheme that employs dynamic programming (DP) principle to analytically select the modulation scheme online. The scheme uses channel state information from the physical layer and congestion information from the scheduling layer to select a modulation rate. This online selection maximizes throughput while saving energy and preventing congestion. The simulation results indicate that an increase in throughput by 96% and energy-efficiency by 131% is observed when compared to the Receiver Based AutoRate (RBAR) protocol

Predictive Congestion Control MAC Protocol for Wireless Sensor Networks

Available congestion control schemes, for example transport control protocol (TCP), when applied to wireless networks results in a large number of packet drops, unfairness with a significant amount of wasted energy due to retransmissions. To fully utilize the hop by hop feedback information, a suite of novel, decentralized, predictive congestion control schemes are proposed for wireless sensor networks in concert with distributed power control (DPC). Besides providing energy efficient solution, embedded channel estimator in DPC predicts the channel quality. By using the channel quality and node queue utilizations, the onset of network congestion is predicted and congestion control is initiated. Stability of the hop by hop congestion control is demonstrated by using a Lyapunov-based approach. Simulation results show that the proposed schemes result in fewer dropped packets than a network without the hop-by-hop congestion control, better fairness index and network efficiency, higher aggregate throughput, and smaller end-to-end delays over the other available schemes like IEEE 802.11 protocol

Predictive Congestion Control Protocol for Wireless Sensor Networks

Available congestion control schemes, for example transport control protocol (TCP), when applied to wireless networks, result in a large number of packet drops, unfair scenarios and low throughputs with a significant amount of wasted energy due to retransmissions. To fully utilize the hop by hop feedback information, this paper presents a novel, decentralized, predictive congestion control (DPCC) for wireless sensor networks (WSN). The DPCC consists of an adaptive flow and adaptive back-off interval selection schemes that work in concert with energy efficient, distributed power control (DPC). The DPCC detects the onset of congestion using queue utilization and the embedded channel estimator algorithm in DPC that predicts the channel quality. Then, an adaptive flow control scheme selects suitable rate which is enforced by the newly proposed adaptive backoff interval selection scheme. An optional adaptive scheduling scheme updates weights associated with each packet to guarantee the weighted fairness during congestion. Closed-loop stability of the proposed hop-by-hop congestion control is demonstrated by using the Lyapunov-based approach. Simulation results show that the DPCC reduces congestion and improves performance over congestion detection and avoidance (CODA) [3] and IEEE 802.11 protocols

Reducing Common-Mode Voltage in Three-Phase Sine-Triangle PWM with Interleaved Carriers

Interleaving PWM waveforms is a proven method to reduce ripple in dc-dc converters. The present work explores interleaving for three-phase motor drives. Fourier analysis shows that interleaving the carriers in conventional uniform PWM significantly reduces the common-mode voltage. New DSP hardware supports interleaving directly with changes to just two registers at setup time, so no additional computation time is needed during operation. The common-mode voltage reduction ranges from 36% at full modulation to 67% when idling with zero modulation. Third harmonic injection slightly reduces the advantage (to 26% at full modulation). However, the maximum RMS common-mode voltage is still less than 20% of the bus voltage under all conditions. Low-voltage experimental results support the findings

Distributed Power Control for Cellular Networks in the Presence of Channel Uncertainties

In this paper, a novel distributed power control (DPC) scheme for cellular network in the presence of radio channel uncertainties such as path loss, shadowing, and Rayleigh fading is presented. Since these uncertainties can attenuate the received signal strength and can cause variations in the received Signal-to-Interference ratio (SIR), a new DPC scheme, which can estimate the slowly varying channel uncertainty, is proposed so that a target SIR at the receiver can be maintained. Further, the standard assumption of a constant interference during a link\u27s power update used in other works in the literature is relaxed. A CDMA-based cellular network environment has been developed to compare the proposed scheme with earlier approaches. The results show that our DPC scheme can converge faster than others by adapting to the channel variations. In the presence of channel uncertainties, our DPC scheme renders lower outage probability while consuming significantly low power per active mobile user compared with other schemes that are available in the literature

Dynamic Channel Allocation in Wireless Networks Using Adaptive Learning Automata

The bandwidth utilization of a single channel-based wireless networks decreases due to congestion and interference from other sources and therefore transmission on multiple channels are needed. In this paper, we propose a distributed dynamic channel allocation scheme for wireless networks using adaptive learning automata whose nodes are equipped with single radio interfaces so that a more suitable channel can be selected. The proposed scheme, adaptive pursuit reward-inaction, runs periodically on the nodes, and adaptively finds the suitable channel allocation in order to attain a desired performance. A novel performance index, which takes into account the throughput and the energy consumption, is considered. The proposed scheme is adaptive in the sense that probabilities in the each step are updated as a function of the error in the performance index. The extensive simulation results in static and mobile environments provide that using the proposed scheme for channel allocation in the multiple channel wireless networks significantly improves the throughput, drop rate, energy consumption per packet and fairness index

Route Aware Predictive Congestion Control Protocol for Wireless Sensor Networks

Congestion in wireless sensor networks (WSN) may lead to packet losses or delayed delivery of important information rendering the WSN-based monitoring or control system useless. In this paper a routing-aware predictive congestion control (RPCC) yet decentralized scheme for WSN is presented that uses a combination of a hop by hop congestion control mechanism to maintain desired level of buffer occupancy, and a dynamic routing scheme that works in concert with the congestion control mechanism to forward the packets through less congested nodes. The proposed adaptive approach restricts the incoming traffic thus preventing buffer overflow while maintaining the rate through an adaptive back-off interval selection scheme. In addition, the optimal routing scheme diverts traffic from congested nodes through alternative paths in order to balance the load in the network, alleviating congestion. This load balancing of the routes will even out the congestion level throughout the network thus increasing throughput and reducing end to end delay. Closed-loop stability of the proposed hop-by-hop congestion control is demonstrated by using the Lyapunov-based approach. Simulation results show that the proposed scheme results in reduced end-to-end delays

RFID-Based Smart Freezer

This paper presents a novel radio-frequency identification (RFID)-based smart freezer using a new inventory-management scheme for extremely low temperature environments. The proposed solution utilizes backpressure inventory control, systematic selection of antenna configuration, and antenna power control. The proposed distributed-inventory-control (DIC) scheme dictates the amount of items transferred through the supply chain. when a high item visibility is ensured, the control scheme maintains the desired level of inventory at each supply-chain echelon. The performance of the DIC scheme is guaranteed using a Lyapunov-based analysis. The proposed RFID antenna-configuration design methodology coupled with locally asymptotically stable distributed power control ensures a 99% read rate of items while minimizing the required number of RFID antennas in the confined cold chain environments with non-RF-friendly materials. The proposed RFID-based smart-freezer performance is verified through simulations of supply chain and experiments on an industrial freezer testbed operating at -100degF

Distributed Power Control of Cellular Networks in the Presence of Channel Uncertainties

A novel distributed power control (DPC) scheme for cellular networks in the presence of radio channel uncertainties such as path loss shadowing, and Rayleigh fading is presented. Since these uncertainties can attenuate the received signal strength and can cause variations in the received Signal-to-lnterference ratio (SIR), the proposed DPC scheme maintains a target SIR at the receiver provided the uncertainty is slowly varying with time. The DPC estimates the time varying nature of the channel quickly and uses the information to arrive at a suitable transmitter power value . Further, the standard assumption of a constant interference during a link\u27s power update used in other work in the literature is relaxed. A CDMA-hased celluar network environment is used to compare the proposed scheme with earlier approaches. The results show that our DPC scheme can converge faster than others by adapting to the channel variations. The proposed DPC scheme can render outage prohability of 5 to 30% in the presence of uncertainties compared with other schemes of 50 to 90% while consuming law power per active mobile user. In other words, the proposed DPC scheme allows significant increase in network capacity while consuming low- power values even when the channel is uncertain