Earticle

One of the four major processes of an autonomic computing system is to free people from discovering, recovering, and failures, this process is called self-healing. Systems designed to be self-healing are able to heal themselves at runtime in response to changing environmental or operational circumstances. Thus, the goal is to avoid catastrophic failure through prompt execution of remedial actions. This paper proposes a self-healing mechanism that monitors, diagnoses and heals its own internal problems using self-awareness as contextual information. The self-management system that encapsulates the self-healing mechanism related to reliability improvement addresses: (1) Monitoring layer, (2) Diagnosis & Decision Layer, and (3) Adaptation Layer, in order to perform self-diagnosis and self-healing. To confirm the effectiveness of self-healing mechanism, practical experiments are conducted with a prototype system.

As the main computing paradigm for resource-intensive scientific applications, Grid[1] enables resource sharing and dynamic allocation of computational resources. Large-scale grids are normally composed of huge numbers of components from different sites, which increases the requirements of workflows and quality of service (QoS) upon these workflows as many of these components have real-time requirements. In this paper, we describe our web services based QoS-aware workflow management system(WfMS) from GridCC project[7] and show how this WfMS can aid to ensure workflows meet the pre-defined QoS requirements and optimise them accordingly.

The vision of ubiquitous delivery of TV streams to the masses at high quality is tantalizing. However, today, TV streaming is either limited to fixed wired outlets (IPTV), or it is distributed over DVB-x but the required receivers are not built into their devices. Wireless mesh networks have the potential to bridge this gap, as they can receive the TV from either technology and forward it over multiple hops to the user devices that are today equipped with 802.11 cards by default. This paper describes the set up of a TV streaming over the Magnets mesh network deployed in the city of Berlin. Initial performance evaluations on the Magnets backbone and the Magnets indoor mesh show that a combination of careful engineering and multi-card wireless routers can provide sufficient bandwidth to support TV streaming over wireless networks.

This paper presents our work on a service framework for supporting pervasive computing systems. In our vision, a novel mobile service based on pervasive computing requires to provide high accessibility regardless of computing platform and user context. From that point of view, user interface is one of key issues to achieve the vision. Therefore, we discuss technical challenge such as adaptation and context-awareness in terms of user interface. In this paper, we described the requirements and design for the service framework, and its application through explaining a possible scenario. Then we identified diverse modality as a technical challenge for achieving such mobile service and applied media conversion for adapting data representation to each particular modality. Besides, we carried out user trial using an experimental prototype. The results of the trial show the proposed approach for modality adaptation is beneficial to users in some aspect through usability and feasibility analyses.

Tree depth and load balancing are two main metrics in overlay multicast network. Optimizing the two metrics with lightweight overhead is important for live media streaming. This paper proposes one scheme to construct optimized overlay multicast with short tree depth and load balancing via short random walk. The key idea is the preferential random walk based on fitness function in which the tree depth and load balancing metrics are defined as parameters with weighted coefficients. Simulations and experiments show that the fitness function is valid and optimized overlay network could be constructed via preferential random walk. We also find the local and global optimized results occur at some middle value of coefficient between 0 and 1, which is not consist with our intuitions that optimized result with single metric should occur at the boundary of coefficient(0 or 1.0).

Wireless Sensor Networks (WSNs) have been widely used in environment monitoring to collect useful information. Packet broadcasting is an essential communication behavior for establishing a communication path from sink node to an interested region of sensor nodes. ZBP is a cellular based broadcast protocol, and it successfully outperformed simple flooding manner broadcasting and common cellular based approach in two main aspects: first it reduced the number of sensor nodes that forward transmission packets and thus save energy consumption; second, it can efficiently avoid collision by properly arranging broadcasting schedule. However it still faces broadcasting failure caused by blank region of sensors. This paper improves ZBP by introducing an energy efficient recovery mechanism which recovers broadcasting when blank region interrupts the request forwarding. Compared with the simple over-network flooding recovery used by ZBP, our proposed protocol can reduce much energy consumption.

To implement transmit beamforming, which is an effective way of leveraging the diversity gains, for multiple-input single-output orthogonal frequency division multiplexing (MISOOFDM) systems, (partial) channel state information is required at the transmitter. In this paper, we present a new limited feedback scheme in MISO-OFDM systems with transmit beamforming. By dividing the total subcarriers of an OFDM symbol into a series of clusters, from the codebook we choose the “proper” one, which minimizes the average bit error rate (BER) per subcarrier of the considered cluster, as the beamforming vector for this cluster. The scheme can reduce the feedback overhead remarkably while obtain good BER performance. Further, a simple sub-optimal algorithm exploiting the correlation of channel frequency responses at different ubcarriers is proposed to avoid exhaustive search in the optimal solution. The complexity analysis and simulations show that the proposed method has low computational complexity and provides improvement over the existing schemes.

A new decoding method based on IR_HARQ scheme that uses rate-compatible LDPC codes as the FEC codes is presented in this paper. This method can use the former decoding result, which can improve the performance of decoding scheme. This paper also evaluates the new decoding method by simulation. The results show that better performance both on system throughput and iterative numbers can be obtained.

Semi-structured documents formatted with the extensible markup language (XML) are gaining wide use by a whole range of applications including E-Commerce, E-Business, E-Science, Digital Libraries (DL), File Sharing, and in the last years especially by applications for Peer-to-Peer (P2P) systems. P2P architectures have been identified as an efficient means of ad-hoc collaboration and information sharing among large, diverse, and dynamic sets of user. However, current P2P search engines for XML-documents lack the use of information retrieval methods to efficiently search XML collections for relevant information. This article proposes a search engine for P2P systems that applies an extension of the vector space model and exploits structural information to compute relevance of XML-documents, and thus may significantly improve retrieval performance. We concentrate on the cooperation of peers that perform a distributed query execution through cooperated retrieval and ranking of dynamic XML documents. The interaction between the participating peers is based on a structured P2P-network and uses an adaption of the DHT-algorithm Kademlia.

This paper presents an efficient clustering algorithm for faults identification in large telecommunication networks. The alarms and faults in telecommunication networks present some interesting characteristics like storm and cascade of events. For instance, a single fault may result in a large number of alarms, and it is often very difficult to isolate the true cause of a fault. Our algorithm is especially designed for the event correlation problem taking into account comprehensive information about the system behaviour. Our technique is tested and compared with some available clustering algorithms on some samples from both simulated and real data from Ericsson’s network.

As the mobile communication environments grow rapidly, much attention has been paid on the use of spectrum resources. Recently, a new technology called Cognitive Radio (CR) was developed for using the unused spectrum bands efficiently. In the CR system, one possible way to locate these unused spectrum bands is to use so-called spectrum sensing. This technique, however, should be computationally simple and fast in order to catch up with the changing signal parameters. In this paper, we propose a cyclostationary feature based detection technique for spectrum sensing. To improve spectrum sensing performance, the proposed spectrum sensing technique computes the circular correlation of received signal before the cyclostationary feature based detection. Simulation results show that the proposed spectrum sensing technique provides better spectrum sensing performance than cyclostationary feature based detection technique even in the low SNR environment.

In construction project management, ideologies and tasks related to resource supply are more significant than the integrated resources management. Such ideologies and tasks are considered crucial for achieving terms, pricing, quality and the goal of the project. It makes metal work resources even more important and as the target for special management. With these pressing issues in construction project management, the researchers proposed a web based system to improve such management task.