Jinsung Cho

Resource allocation for scalable video broadcast in wireless cellular networks

Video broadcast services have become increasingly popular on packet-based wireless networks, such as 1xEV-DO and HSDPA which support high data rate. In this paper we propose a resource allocation algorithm for scalable video broadcast over such wireless networks. Our algorithm allocates time slots among the video layers of a scalable video and applies adaptive modulation and coding (AMC) to each video layer to maximize the sum of utilities for heterogeneous users with varying QoS requirements. It also considers competing video sessions and allocates time slots among them according to user preferences. Additionally, its polynomial time-complexity allows for online resource allocation that is necessary for real-time video services. Simulation experiments show that our algorithm outperforms a single-layer video broadcast with fixed modulation and coding (FMC), used in broadcast and multicast services (BCMCS) in the CDMA2000 system, and produce a near-optimal allocation.

An energy-efficient transmission strategy for wireless sensor networks

In this work we propose an energy-efficient transmission strategy for wireless sensor networks that operate in a strict energy-constrained environment. Our transmission algorithm consists of two components: a binary-decision based transmission and a channel-aware backoff adjustment. In the binary-decision based transmission, decision on whether to transmit or not is absolutely dependent on the current channel conditions. Specifically, transmission is initiated only when the channel quality exceeds a specified threshold, so that unsuccessful transmissions causing a waste of energy are avoided whenever possible. Using the Markov decision process (MDP) formulation we obtain the optimum threshold for successful transmission. A channel-aware backoff adjustment, the second component of our proposal, is introduced to favor nodes with better channel conditions. By intelligently combining these two ingredients our transmission algorithm attempts to maximize energy efficiency. Extensive simulations are performed to verify the performance of our proposal over fading wireless channels. Numerical results show that our transmission algorithm outperforms the existing approaches in terms of energy efficiency, thereby further prolonging the network lifetime.

Bus encoding for low-power high-performance memory systems

High-performance memory buses consume large energy as they include termination networks, BiCMOS and/or open-drain output. This paper introduces power reduction techniques for memory systems deliberating on burst-mode transfers over the high-speed bus specifications such as Low Voltage BiCMOS (LVT), Gunning Transfer Logic (GTL+) and Stub Series Termination Logic (SSTL_2) which are widely used. The reduction techniques take both the static and the dynamic power consumption into account because most high-performance bus drivers and end-termination networks dissipate significant static power as well. Extensive performance analysis is conducted through mathematical analysis and trace data-driven simulations. We had reduction of 14% with random data and up to 67.5% with trace data.

Energy-Efficient deployment of mobile sensor networks by PSO

Sensor deployment is an important issue in designing sensor networks. In this paper, particle swarm optimization (PSO) approach is applied to maximize the coverage based on a probabilistic sensor model in mobile sensor networks and to reduce cost by finding the optimal positions for the cluster-head nodes based on a well-known energy model. During the coverage optimization process, sensors move to form a uniformly distributed topology according to the execution of algorithm at base station. The simulation results show that PSO algorithm has faster convergence rate than genetic algorithm based method while achieving the goal of energy efficient sensor deployment.

Layered resource allocation for video broadcasts over wireless networks

This paper aims to combine adaptive modulation and coding with layered video coding to improve the quality of video services to users experiencing differing radio conditions, in the context of broadcast and multicast standards such as MBMS and BCMCS. We propose an optimal radio resource allocation algorithm which maximizes a general performance metric for a video session in polynomial time. We show that system-wide optimal resource allocation can be obtained by combining our algorithm with a simple two-step decomposition of the system. In some configurations frequent re-allocations of resource are required, so we also present a sub-optimal allocation algorithm which runs in near linear time. Simulation results show better video quality than existing resource allocation schemes over a range of conditions, and also suggest that the difference between the performance of optimal and suboptimal solutions is less than 3%.

Mobility-Assisted Relocation for Self-Deployment in Wireless Sensor Networks

Sensor network deployment is very challenging due to the hostile and unpredictable nature of environments. The field coverage of wireless sensor networks (WSNs) can be enhanced and consequently network lifetime can be prolonged by optimizing the sensor deployment with a finite number of mobile sensors. In this paper, we introduce a comprehensive taxonomy for WSN self-deployment in which three sensor relocation algorithms are proposed to match the mobility degree of sensor nodes, particle swarm optimization based algorithm (PSOA), relay shift based algorithm (RSBA) and energy efficient fuzzy optimization algorithm (EFOA). PSOA regards the sensors in the network as a swarm, and reorganizes the sensors by the particle swarm optimization (PSO) algorithm, in the full sensor mobility case. RSBA and EFOA assume relatively limited sensor mobility, i.e., the movement distance is bounded by a threshold, to further reduce energy consumption. In the zero mobility case, static topology control or scheduling schemes can be used such as optimal cluster formation. Simulation results show that our approaches greatly improve the network coverage as well as energy efficiency compared with related works.

Active caching: a transmission method to guarantee desired communication reliability in wireless sensor networks

Due to the high packet loss rate during multi-hop transmissions in wireless sensor networks, more reliable end-to-end data transmission is desirable. Because wireless sensor network applications require various levels of communication reliability (CR), the end-to-end data transmission should satisfy the desired CR of the applications. In this letter, we propose a flexible loss recovery mechanism for sensor network applications with various CRs. The proposed scheme caches data packets at intermediate nodes over routing paths computed by CR to retransmit lost packets during multi-hop transmissions. Because the proposed scheme presents a tradeoff between end-to-end delays and memory requirements dependent on CR, it can be used flexibly in various sensor network applications.

VIP Bridge: Integrating Several Sensor Networks into One Virtual Sensor Network

Some applications need to collect information from several different sensor networks to provide comprehensive services. In order to simplify the complexity of dealing with heterogeneous sensor networks, a uniform interface should be provided for users. This paper describes a novel approach to integrate these different sensor networks into one virtual sensor network. Users can easily query data through this virtual sensor network. By having the comparison and prototyping work we claim that our new approach can cover most advantages of related researches

A load-balancing and energy-aware clustering algorithm in wireless ad-hoc networks

Wireless ad-hoc network is a collection of wireless mobile nodes dynamically forming a temporary communication network without the use of any existing infrastructure or centralized administration. It is characterized by both highly dynamic network topology and limited energy. So, the efficiency of MANET depends not only on its control protocol, but also on its topology and energy management. Clustering strategy can improve the performance of flexibility and scalability in the network. With the aid of graph theory, genetic algorithm and simulated annealing hybrid optimization algorithm, this paper proposes a new clustering strategy to perform topology management and energy conservation. Performance comparison is made between the original algorithms and our two new algorithms, namely an improved weighting clustering algorithm and a novel Genetic Annealing based Clustering Algorithm (GACA), in the aspects of average cluster number, topology stability, load-balancing and network lifetime. The experimental results show that our clustering algorithms have a better performance on average.

Connecting heterogeneous sensor networks with IP based wire/wireless networks

Several heterogeneous sensor networks which are physically deployed in different places sometimes need to be integrated over IP based wire/wireless networks into one virtual sensor networks to provide meaningful services for users. However, how to connect sensor networks with IP based networks comes out to be an aforethought issue for this integration problem. In this paper, we analyze and compare all the existing solutions for connecting sensor networks with TCP/IP network, then based on the analysis result we present the basic design principle and key idea for connecting sensor networks with TCP/IP network. After comparing with related researches we claim that our solution can cover most of the benefits of related researches