A cache-based mobility-aware scheme for real-time continuous media delivery in wireless networks

Providing real-time or continuous media (CM) application services in wireless networks poses a significant challenge, as it requires timely delivery of data in a best-effort network. In this paper, we propose a cache-based scheme for mobility-aware, CM applications. The proposed scheme exploits a previously proposed caching strategy to complement Mobile-IP by placing services closer to migrated mobile nodes. The central idea of this work is based on the migration of sessions in order to facilitate uninterrupted delivery of CM in mobile environments. The performance of the proposed scheme is investigated by simulation studies. In particular, the effect of the proposed scheme on several QoS parameters under varying conditions of mobility and CM data is measured.

A generalised cost-aware caching scheme for caching continuous media objects in best-effort network environments

In this paper, we investigate the potential of caching to improve QoS in the context of continuous media applications over wired best-effort networks. We propose the use of a flexible caching scheme, called GD-Multi in caching continuous media (CM) objects. An important novel feature of our scheme is the provision of user or system administrator inputs in determining the cost function. Based on the proposed flexible cost function, Multi, an improvised Greedy Dual (GD) replacement algorithm called GD-multi (GDM) has been developed for layered multi-resolution multimedia streams. The proposed Multi function takes receiver feedback into account. We investigate the influence of parameters such as loss rate, jitter, delay and area in determining a proxy’s cache contents so as to enhance QoS perceived by clients. Simulation studies show improvement in QoS perceived at the clients in accordance to supplied optimisation metrics. From an implementation perspective, signalling requirements for carrying QoS feedback are minimal and fully compatible with existing RTSP-based Internet applications.

An effective semi-supervised clustering framework integrating pairwise constraints and attribute preferences

Both the instance level knowledge and the attribute level knowledge can improve clustering quality, but how to effectively utilize both of them is an essential problem to solve. This paper proposes a wrapper framework for semi-supervised clustering, which aims to gracely integrate both kinds of priori knowledge in the clustering process, the instance level knowledge in the form of pairwise constraints and the attribute level knowledge in the form of attribute order preferences. The wrapped algorithm is then designed as a semi-supervised clustering process which transforms this clustering problem into an optimization problem. The experimental results demonstrate the effectiveness and potential of proposed method.

Multi-level virtual ring : an architecture for content routing in wireless sensor network

Two main problems prevent the deployment of content delivery in a wireless sensor network: the address, which is widely used in the Internet as the identifier, is meaningless in wireless network, and the routing efficiency is a big concern in wireless sensor network. This paper presents an embedded multi-level ring (MVR) structure to address those two problems. The MVR uses names rather than addresses to identify sensor nodes. The MVR routes packets on the name identifiers without being aware the location. Some sensor nodes are selected as the backbone nodes and are placed on the different levels of the virtual rings. MVR hashes nodes and contents identifiers, and stores them at the backbone nodes. MVR takes the cross-level routing to improve the routing efficiency. Further, MVR is constructed decentralized and runs on the mobile nodes themselves, requiring no central control. Experiments using ns2 simulator for up to 200 nodes show that the storage and bandwidth requirements of MVR grow slowly with the size of the network. Furthermore, MVR has demonstrated as self-administrating, fault-tolerant, and resilient under the different workloads. We also discuss alternative implementation options, and future work.

Fuzzy clustering of color and texture features for image segmentation: a study on satellite image retrieval

In this paper, a new image segmentation approach that integrates color and texture features using the fuzzy c-means clustering algorithm is described. To demonstrate the applicability of the proposed approach to satellite image retrieval, an interactive region-based image query system is designed and developed. A database comprising 400 multispectral satellite images is used to evaluate the performance of the system. The results are analyzed and discussed, and a performance comparison with other methods is included. The outcomes reveal that the proposed approach is able to improve the quality of the segmentation results as well as the retrieval performance.

Application of fuzzy ARTMAP and fuzzy c-means clustering to pattern classification with incomplete data

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CodePipe : an opportunistic feeding and routing protocol for reliable multicast with pipelined network coding

Multicast is an important mechanism in modern wireless networks and has attracted significant efforts to improve its performance with different metrics including throughput, delay, energy efficiency, etc. Traditionally, an ideal loss-free channel model is widely used to facilitate routing protocol design. However, the quality of wireless links would be affected or even jeopardized by many factors like collisions, fading or the noise of environment. In this paper, we propose a reliable multicast protocol, called CodePipe, with advanced performance in terms of energy-efficiency, throughput and fairness in lossy wireless networks. Built upon opportunistic routing and random linear network coding, CodePipe not only simplifies transmission coordination between nodes, but also improves the multicast throughput significantly by exploiting both intra-batch and inter-batch coding opportunities. In particular, four key techniques, namely, LP-based opportunistic routing structure, opportunistic feeding, fast batch moving and inter-batch coding, are proposed to offer substantial improvement in throughput, energy-efficiency and fairness. We evaluate CodePipe on ns2 simulator by comparing with other two state-of-art multicast protocols, MORE and Pacifier. Simulation results show that CodePipe significantly outperforms both of them.

Hybrid image segmentation using fuzzy clustering algorithms satellite imagery searching and retrieval

Satellite image processing is a complex task that has received considerable attention from many researchers. In this paper, an interactive image query system for satellite imagery searching and retrieval is proposed. Like most image retrieval systems, extraction of image features is the most important step that has a great impact on the retrieval performance. Thus, a new technique that fuses color and texture features for segmentation is introduced. Applicability of the proposed technique is assessed using a database containing multispectral satellite imagery. The experiments demonstrate that the proposed segmentation technique is able to improve quality of the segmentation results as well as the retrieval performance.

Adaptation of LEACH routing protocol to cognitive radio sensor networks

One of the drawbacks of LEACH protocol is the uncontrolled selection of cluster heads which, in some rounds, leads to the concentration of them in a limited area due to the randomness of the selection procedure. LEACH-C is a variant of LEACH that uses a centralized clustering algorithm and forms good clusters through sink control. According to experimental results, the IEEE 802.15.4 packets are damaged by WLAN interferences in ISM band. It seems that, sensor nodes equipped with cognitive radio capabilities can overcome this problem. In cognitive radio sensor networks (CRSN), routing must be accompanied by channel allocation. This requires spectrum management which can be devolved to cluster heads. For this networks, new duty cycle mechanisms must be designed that jointly consider neighbor discovery, and spectrum sensing/allocation. Cluster-based network architecture is a good choice for effective dynamic spectrum management. In such architecture, cluster heads have a proper spatial distribution and are optimally located all over the network. In this paper, using the physical layer information and preserving the feature of random cluster head selection in LEACH, it has been tried to both move the position of cluster heads to appropriate locations and make their quantity optimal. The simulation results show that the transferal of cluster heads to appropriate locations increases the network lifetime significantly though this comes at the price of early instability appearance. By considering the energy level in cluster head election algorithm, one can overcome the network stability issues too. However, this will move the cluster heads away from their appropriate locations. © 2012 IEEE.