Very low bit-rate video coding focusing on moving regions using three-tier arbitrary-shaped pattern selection algorithm

Very low bit-rate video coding using patterns to represent moving regions in macroblocks exhibits good potential for improved coding efficiency. Recently an Arbitrary Shaped Pattern Selection (ASPS) algorithm and its Extended version(EASPS) were presented, that used a dynamically extracted set of patterns, of the two different sizes, based on actual video content. These algorithms, like other pattern matching algorithms failed to capture a large number of active-region macroblocks (RMB) especially when the object moving regions is relatively larger in a video sequence. As the size of the moving object may vary, superior coding performance is achievable by using dynamically extracted patterns of a larger size. This paper, proposes a three-tier Arbitrary Shaped Pattern Selection (ASPS-3) algorithm that uses three different pattern sizes for very low bit ate coding. Experimental results show that ASPS-3 exhibits better performance compared with other pattern matching algorithms, including the low-bit rate video coding standard H.263

GridSim: A Toolkit for the Modeling and Simulation of Distributed Resource Management and Scheduling for Grid Computing

Clusters, grids, and peer-to-peer (P2P) networks have emerged as popular paradigms for next generation parallel and distributed computing. The management of resources and scheduling of applications in such large-scale distributed systems is a complex undertaking. In order to prove the effectiveness of resource brokers and associated scheduling algorithms, their performance needs to be evaluated under different scenarios such as varying number of resources and users with different requirements. In a grid environment, it is hard and even impossible to perform scheduler performance evaluation in a repeatable and controllable manner as resources and users are distributed across multiple organizations with their own policies. To overcome this limitation, we have developed a Java-based discrete-event grid simulation toolkit called GridSim. The toolkit supports modeling and simulation of heterogeneous grid resources (both time- and space-shared), users and application models. It provides primitives for creation of application tasks, mapping of tasks to resources, and their management. To demonstrate suitability of the GridSim toolkit, we have simulated a Nimrod-G like grid resource broker and evaluated the performance of deadline and budget constrained cost- and time-minimization scheduling algorithms

A directionally based bandwidth reservation scheme for call admission control

This paper proposes a new advanced Call Admission Control(CAC) strategy involving for the first time, a bandwidth reservation scheme that is influenced by the direction attribute of a mobile terminal (MT). Aside from the Quality-of-Service (QoS) parameters, the direction attribute plays a key role in efficiently reserving resources for MTs supporting multimedia communications for different QoS classes. The framework for a direction-based CAC system is entirely distributed and may be viewed as a message passing system, where MTs inform their neighbouring base stations (BS) not only of their QoS requirements, but also of their mobility parameters. The base stations then predict future demand and reserve resources accordingly, only admitting those terminals that can be adequately supported. The bandwidth reservation scheme proposed in this paper, integrates the direction attribute into the conventional Guard Channel (GC) scheme. Simulation results prove that this new scheme offers significant improvements in both Call Blocking Probability (CBP) and bandwidth utilization, under a variety of differing traffic conditions

An Algorithm for Network and Data-aware Placement of Multi-Tier Applications in Cloud Data Centers

Today's Cloud applications are dominated by composite applications comprising multiple computing and data components with strong communication correlations among them. Although Cloud providers are deploying large number of computing and storage devices to address the ever increasing demand for computing and storage resources, network resource demands are emerging as one of the key areas of performance bottleneck. This paper addresses network-aware placement of virtual components (computing and data) of multi-tier applications in data centers and formally defines the placement as an optimization problem. The simultaneous placement of Virtual Machines and data blocks aims at reducing the network overhead of the data center network infrastructure. A greedy heuristic is proposed for the on-demand application components placement that localizes network traffic in the data center interconnect. Such optimization helps reducing communication overhead in upper layer network switches that will eventually reduce the overall traffic volume across the data center. This, in turn, will help reducing packet transmission delay, increasing network performance, and minimizing the energy consumption of network components. Experimental results demonstrate performance superiority of the proposed algorithm over other approaches where it outperforms the state-of-the-art network-aware application placement algorithm across all performance metrics by reducing the average network cost up to 67% and network usage at core switches up to 84%, as well as increasing the average number of application deployments up to 18%.Comment: Submitted for publication consideration for the Journal of Network and Computer Applications (JNCA). Total page: 28. Number of figures: 15 figure

Demand-driven movement strategy for moving beacons in distributed sensor localization

n a wireless sensor network, range-free localization with a moving beacon can reduce susceptibility to communication noises while concomitantly eliminate need for large number of expensive anchor nodes that are vulnerable to malicious attacks. This paper presents a moving beacon aided range-free localization technique, which is capable of estimating the location of a sensor with high accuracy. A novel distributed localization scheme is designed to optimally determine beacon movement strategy according to user demand. Superiority of this scheme to the state-of-the-art has been established in terms of location estimation quality, measured by the theoretical expected maximum error and simulated mean error while optimizing the beacon location density or traversal path length