Abstract: In this paper, we assess Quality of Services (QoS) requirements in wireless sensor networks (WSNs).QOS is a key component of the IMS. The QoS for a particular session is determined by a number of factors, such as the maximum bandwidth that can be allocated to the user based on the user’s

Mode (ATM) is designed not only to support a wide range of traffic classes with diverse flow characteristics, but also to guarantee the different quality of service QOS requirements. The QOS may be measured in terms of cell loss probability and maximum cell delay. In this paper, ATM networks

Mode (ATM) is designed not only to support a wide range of traffic classes with diverse flow characteristics, but also to guarantee the different quality of service QOS requirements. The QOS may be measured in terms of cell loss probability and maximum cell delay. In this paper, ATM networks

to the users. To achieve this goal, an efficient grid scheduling algorithm is required. The problem of scheduling on data intensive application in terms of QOS requirements is challenging and it significantly influences the performance of grids. The existing algorithms for scheduling the data intensive

An ad-hoc network is the cooperative engagement of a collection of mobile nodes without the required intervention of any centralized access point or existing infrastructure. In this paper we present Ad-hoc On Demand Distance Vector Routing (AODV), a novel algorithm for the operation of such ad

This paper presents the expected transmission count metric (ETX), which finds high-throughput paths on multi-hop wireless networks. ETX minimizes the expected total number of packet transmissions (including retransmissions) required to successfully deliver a packet to the ultimate destination

is measured in terms of the state, control message processing, and data packet processing, required across the entire network in order to deliver data packets to the members of the group. Our Protocol Independent Multicast (PIM) architecture: (a) maintains the traditional IP multicast service model

With the significant advances in Information and Communications Technology (ICT) over the last half century, there is an increasingly perceived vision that computing will one day be the 5th utility (after water, electricity, gas, and telephony). This computing utility, like all other four existing utilities, will provide the basic level of computing service that is considered essential to meet the everyday needs of the general community. To deliver this vision, a number of computing paradigms have been proposed, of which the latest one is known as Cloud computing. Hence, in this paper, we define Cloud computing and provide the architecture for creating Clouds with market-oriented resource allocation by leveraging technologies such as Virtual Machines (VMs). We also provide insights on market-based resource management strategies that encompass both customer-driven service management and computational risk management to sustain Service Level Agreement (SLA)-oriented resource allocation. In addition, we reveal our early thoughts on interconnecting Clouds for dynamically creating global Cloud exchanges and markets. Then, we present some representative Cloud platforms, especially those developed in industries along with our current work towards realizing market-oriented resource allocation of Clouds as realized in Aneka enterprise Cloud technology. Furthermore, we highlight the difference between High Performance Computing (HPC) workload and Internet-based services workload. We also describe a meta-negotiation infrastructure to establish global Cloud

We present a suite of algorithms for self-organization of wireless sensor networks, in which there is a scalably large number of mainly static nodes with highly constrained energy resources. The protocols further support slow mobility by a subset of the nodes, energy-efficient routing, and formation of ad hoc subnetworks for carrying out cooperative signal processing functions among a set of the nodes.

This paper describes a self-organizing, multihop, mobile radio network, which relies on a code division access scheme for multimedia support. In the proposed network architecture, nodes are organized into nonoverlapping clusters. The clusters are independently controlled and are dynamically reconfigured as nodes move. This network architecture has three main advantages. First, it provides spatial reuse of the bandwidth due to node clustering. Secondly, bandwidth can be shared or reserved in a controlled fashion in each cluster. Finally, the cluster algorithm is robust in the face of topological changes caused by node motion, node failure and node insertion/removal. Simulation shows that this architecture provides an efficient, stable infrastructure for the integration of different types of traffic in a dynamic radio network. 1.