Pervasive computing at tableside : a wireless web-based ordering system

Purpose &ndash; The purpose of this paper is to introduce a wireless web-based ordering system called iMenu in the restaurant industry. Design/methodology/approach &ndash; By using wireless devices such as personal digital assistants and WebPads, this system realizes the paradigm of pervasive computing at tableside. Detailed system requirements, design, implementation and evaluation of iMenu are presented.Findings &ndash; The evaluation of iMenu shows it explicitly increases productivity of restaurant staff. It also has other desirable features such as integration, interoperation and scalability. Compared to traditional restaurant ordering process, by using this system customers get faster and better services, restaurant staff cooperate more efficiently with less working mistakes, and enterprise owners thus receive more business profits. Originality/value &ndash; While many researchers have explored using wireless web-based information systems in different industries, this paper presents a system that employs wireless multi-tiered web-based architecture to build pervasive computing systems. Instead of discussing theoretical issues on pervasive computing, we focus on practical issues of developing a real system, such as choosing of web-based architecture, design of input methods in small screens, and response time in wireless web-based systems.<br /

Building reliable distributed systems

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Efficient algorithm for mobile multicast using anycast group

The authors present a novel and efficient multicast algorithm that aims to reduce delay and communication cost for the registration between mobile nodes and mobility agents and solicitation for foreign agent services based on the mobile IP. The protocol applies anycast group technology to support multicast transmissions for both mobile nodes and home/foreign agents. Mobile hosts use anycast tunnelling to connect to the nearest available home/foreign agent where an agent is able to forward the multicast messages by selecting an anycast route to a multicast router so as to reduce the end-to-end delay. The performance analysis and experiments demonstrated that the proposed algorithm is able to enhance the performance over existing remote subscription and bidirectional tunnelling approaches regardless of the locations of mobile nodes/hosts<br /

Protecting web services with service oriented traceback architecture

Service oriented architecture (SOA) is a way of reorganizing software infrastructure into a set of service abstracts. In the area of applying SOA to Web service security, there have been some well defined security dimensions. However, current Web security systems, like WS-Security are not efficient enough to handle distributed denial of service (DDoS) attacks. Our new approach, service oriented traceback architecture (SOTA), provides a framework to be able to identify the source of an attack. This is accomplished by deploying our defence system at distributed routers, in order to examine the incoming SOAP messages and place our own SOAP header. By this method, we can then use the new SOAP header information, to traceback through the network the source of the attack. According to our experimental performance evaluations, we find that SOTA is quite scaleable, simple and quite effective at identifying the source.<br /

Corners-based composite descriptor for shapes

In this paper, a composite descriptor for shape retrieval is proposed. The composite descriptor is obtained based upon corner-points and shape region. In an earlier paper, we proposed a composite descriptor based on shape region and shape contour, however, the descriptor was not effective for all perspective and geometric transformations. Hence, we modify the composite descriptor by replacing contour features with corner-points features. The proposed descriptor is obtained from Generic FourierDescriptors (GFD) of the shape region and the GFD ofthe corner-points. We study the performance of the proposed composite descriptor. The proposed method is evaluated using Item S8 within the MPEG-7 Still Images Content Set. Experimental results show that the proposed descriptor is effective.<br /

Mark-aided distributed filtering by using neural network for DDoS defense

Currently Distributed Denial of Service (DDoS) attacks have been identified as one of the most serious problems on the Internet. The aim of DDoS attacks is to prevent legitimate users from accessing desired resources, such as network bandwidth. Hence the immediate task of DDoS defense is to provide as much resources as possible to legitimate users when there is an attack. Unfortunately most current defense approaches can not efficiently detect and filter out attack traffic. Our approach is to find the network anomalies by using neural network, deploy the system at distributed routers, identify the attack packets, and then filter them. The marks in the IP header that are generated by a group of IP traceback schemes, Deterministic Packet Marking (DPM)/Flexible Deterministic Packet Marking (FDPM), assist this process of identifying attack packets. The experimental results show that this approach can be used to defend against both intensive and subtle DDoS attacks, and can catch DDoS attacks&rsquo; characteristic of starting from multiple sources to a single victim. According to results, we find the marks in IP headers can enhance the sensitivity and accuracy of detection, thus improve the legitimate traffic throughput and reduce attack traffic throughput. Therefore, it can perform well in filtering DDoS attack traffic precisely and effectively.<br /

A parallel Euler approach for large-scale biological sequence assembly

Biological sequence assembly is an essential step for sequencing the genomes of organisms. Sequence assembly is very computing intensive especially for the large-scale sequence assembly. Parallel computing is an effective way to reduce the computing time and support the assembly for large amount of biological fragments. Euler sequence assembly algorithm is an innovative algorithm proposed recently. The advantage of this algorithm is that its computing complexity is polynomial and it provides a better solution to the notorious &ldquo;repeat&rdquo; problem. This paper introduces the parallelization of the Euler sequence assembly algorithm. All the Genome fragments generated by whole genome shotgun (WGS) will be assembled as a whole rather than dividing them into groups which may incurs errors due to the inaccurate group partition. The implemented system can be run on supercomputers, network of workstations or even network of PC computers. The experimental results have demonstrated the performance of our system.<br /

A defense system against DDoS attacks by large-scale IP traceback

In this paper, we present a new approach, called Flexible Deterministic Packet Marking (FDPM), to perform a large-scale IP traceback to defend against Distributed Denial of Service (DDoS) attacks. In a DDoS attack the victim host or network is usually attacked by a large number of spoofed IP packets coming from multiple sources. IP traceback is the ability to trace the IP packets to their sources without relying on the source address field of the IP header. FDPM provides many flexible features to trace the IP packets and can obtain better tracing capability than current IP traceback mechanisms, such as Probabilistic Packet Marking (PPM), and Deterministic Packet Marking (DPM). The flexibilities of FDPM are in two ways, one is that it can adjust the length of marking field according to the network protocols deployed; the other is that it can adjust the marking rate according to the load of participating routers. The implementation and evaluation demonstrates that the FDPM needs moderately only a small number of packets to complete the traceback process; and can successfully perform a large-scale IP traceback, for example, trace up to 110,000 sources in a single incident response. It has a built-in overload prevention mechanism, therefore this scheme can perform a good traceback process even it is heavily loaded.<br /

Classifying DDoS packets in high-speed networks

Recently high-speed networks have been utilized by attackers as Distributed Denial of Service (DDoS) attack infrastructure. Services on high-speed networks also have been attacked by successive waves of the DDoS attacks. How to sensitively and accurately detect the attack traffic, and quickly filter out the attack packets are still the major challenges in DDoS defense. Unfortunately most current defense approaches can not efficiently fulfill these tasks. Our approach is to find the network anomalies by using neural network and classify DDoS packets by a Bloom filter-based classifier (BFC). BFC is a set of spaceefficient data structures and algorithms for packet classification. The evaluation results show that the simple complexity, high classification speed and accuracy and low storage requirements of this classifier make it not only suitable for DDoS filtering in high-speed networks, but also suitable for other applications such as string matching for intrusion detection systems and IP lookup for programmable routers.<br /

Giving lectures a voice for a cross-cultural audience

The purpose of this poster is to outline a current research project investigating the value of the inclusion of online audio lectures, in units involving cross-cultural student audiences. This research project arose from two contributing factors: The increase in the number of international students, studying both on and off campus, and the movement for universities to go \u27online\u27.<br /