In next generation wireless networks, Internet service providers (ISPs) are expected to offer services through several wireless technologies (e.g., WLAN, 3G, WiFi, and WiMAX). Thus, mobile computers equipped with multiple interfaces will be able to maintain simultaneous connections with different networks and increase their data communication rates by aggregating the bandwidth available at these networks. To guarantee quality-of-service (QoS) for these applications, this paper proposes a dynamic QoS negotiation scheme that allows users to dynamically negotiate the service levels required for their traffic and to reach them through one or more wireless interfaces. Such bandwidth aggregation (BAG) scheme implies transmission of data belonging to a single application via multiple paths with different characteristics, which may result in an out-of-order delivery of data packets to the receiver and introduce additional delays for packets reordering. The proposed QoS negotiation system aims to ensure the continuity of QoS perceived by mobile users while they are on the move between different access points, and also, a fair use of the network resources. The performance of the proposed dynamic QoS negotiation system is investigated and compared against other schemes. The obtained results demonstrate the outstanding performance of the proposed scheme as it enhances the scalability of the system and minimizes the reordering delay and the associated packet loss rate.

The transmission of high quality video requires high bandwidth. Ensuring constantly high bandwidth in wireless environments is a challenging task given constraints in the current wireless network resources. Current mobile computers are equipped with multiples wireless interfaces that can be used to improve the video quality by aggregating the bandwidth of these interfaces. Such Bandwidth Aggregation (BAG) approach involves multiple paths in communication and gives rise to a number of issues related to the management of the Service Level Agreement (SLA) and packet reordering. To guarantee an efficient and fair management of SLA, this paper presents a bandwidth aggregation-aware QoS negotiation mechanism that enables users to dynamically negotiate their desired service levels and to reach them through the use of bandwidth aggregation. This operation is performed while ensuring a fair use of the network resources among all competing users. To cope with packet reordering, a new scheduling strategy is presented. The performance evaluation of the proposed bandwidth aggregation-aware QoS negotiation scheme and the proposed scheduling algorithm are conducted via simulations and the results are discussed.

Users in next generation wireless networks are expected to be highly dynamic while maintaining connectivity through different devices with different processing and communication capabilities. In wireless environments, bandwidth is scarce and channel conditions are time-varying. To guarantee quality of service (QoS) to users roaming between heterogeneous wireless networks, a dynamic QoS negotiation mechanism, which allows users to dynamically negotiate their service-levels with the network, is required. Several protocols for dynamic service level negotiation have been proposed, each focusing on a particular mode. This paper presents an overview of these protocols and discusses their limitations. To alleviate these shortcomings, a dynamic QoS negotiation scheme to allow users to change their service levels in response to changes in both network conditions and their own resource requirements is proposed. In the proposed scheme, upon an intra-domain handoff of a mobile node, the visited access point consults the previously used access point to confirm the legitimacy of the service negotiation request issued by the mobile node. The performance of the proposed scheme has been investigated and compared with other dynamic negotiation approaches. It was demonstrated that the proposed scheme outperforms the state-of-the-art method, in terms of the signaling overhead and data storage, at the expense of a slight increase in the overall negotiation delay.

This paper explores the use of the fuzzy C-means clustering algorithm for inferring functional relationships among proteins from their phylogenetic profiles. We conducted a series of experiments using phylogenetic profiles provided by the Cluster of Orthologous Groups of Proteins (COG) database. Experimental results demonstrate that the increasing expressiveness of fuzzy C-means enables the discovery of functional relationships on E.coli operons which traditional methods fail to detect