Abstract:COBOL, a traditional language, has been presented for more than 50 years. There are at least 100 billion lines of legacy codes written in COBOL up to now. An effective way to maintain these legacy codes is to translate them into modern languages, such as Java. While translating, it is a key-step to eliminate ‘OTO’and‘ERFORM’and their compound control structures in COBOL programs. A method which uses ‘witch’and ‘hile’statements is proposed in this paper instead of ‘OTO’and ‘ERFORM’and their compound control structures. It preserves the readability because the target Java program has the similar control structures. The code size of the target program expands only 2 times in average. This method is applied in the ‘C2J translation system’ It is proved sound and effective since 4 million lines of real COBOL program have been translated and its target program has passed the test.

Abstract:To meet the system scheduling requirements of open hybrid real-time systems, an open adaptive real-time scheduling framework, called OARtS (open adaptive real-time scheduling), is presented in this paper, which comprises three key components: accept control, scheduling server and adaptive control. To guarantee the schedulability in the open environment, OARtS only accepts the task whose computing bandwidth requirement is no higher than the system's spare one. To schedule multi-constraint tasks, a two-layer scheduling mechanism is introduced. In the mechanism, the scheduling server components provide concurrent scheduling mechanism for multi-constraint tasks, and each of them is assigned to a bandwidth-independent computing bandwidth and has its specific scheduling policy to schedule its own task queue. To adapt to the change in the open environment, the adaptive control tries to tune the real-time service level so as to make full use of the system computing capability; to adapt to the uncertainty of execution time of the soft real-time task, a fuzzy control engine is used to regulate the task's computing bandwidth according to fuzzy rules of the scheduling error so as to eliminate the scheduling error and to get a satisfactory soft real-time performance.

Abstract:Existing distributed real-time cooperative systems mainly use operation transformation technique to provide concurrency control service. But the performance of a run-time system will be degraded when the system produces a large amount of collaborative data. A novel concurrency control framework named madOPT based on collaborative data objects is then proposed in this paper. madOPT resolves conflicts by utilizing operation semantics of the accessed data objects. In addition, it integrates a data transmission framework with an operation transformation method and allows the running system to load the data objects dynamically. The enhancement of madOPT over dOPT (distributed operation transformation) is that it reduces the number of queries in operation log during an operation transformation. It takes object attributes as the granularity of concurrency control and thus can support graph and image objects. It also adopts multicast agent to improve the efficiency of data distribution as well as the performance of the system.

Abstract:Heterogeneous computing environments have been widely used in real-time embedded systems. Efficient task scheduling is essential for achieving high performance in the synthesis of embedded systems. The problem has been proved to be NP-complete and mainly heuristic algorithms which often have room for improvement exist. In this paper, an algorithm called the dynamic BLevel first (DBLF) has been presented. The DBLF algorithm selects the ready task with a maximum Blevel (n_i) at each step and assigns the selected task to a processor in an insertion mode. The task is assigned to the suitable processor that satisfies the precedence sequence and has the minimum earliest-finish-time (EFT) of the task. When the EFT costs are equal, the task is firstly assigned to the processor which has the least utilization. Comparied with the related work, the result shows that the DBLF algorithm significantly surpasses the previous approaches in scheduling length.

Abstract:This paper aims to introduce a new representation framework of cognitive state of agents, which includes depictions for intention, belief, and goal, and supplies a necessary theoretical basis for constructing agent architecture. In this formalization, all intentions for a goal form a structure with two orders, one represents the temporal order and the other represents the relevant relations among intentions. At the same time, this paper investigates the relationships among beliefs, intentions, and goals. Since this framework gets rid of modal operators to depict intention, intention base, temporal and relevant relation are be adopted to represent intention when agents are constructed, which can narrow the gap between the agent model and agent architecture.

Abstract:An algorithm for color image segmentation, based on color and spatial information is proposed in this paper. First, color quantization is performed on an image based on the proposed color coarseness metric, and then an incremental region growing method is exploited to find the spatial connectivity of pixels with similar colors to form the initial segmented regions. Second, the initial regions are hierarchically merged based on the region distance defined by the color and spatial information. A criteria is proposed to decide the termination of the merging process. Finally, the erosion and dilation operators are used to smooth the edges of the segmented regions. The experimental results demonstrate that the color image segmentation results of the proposed approach hold favorable consistency in terms of human perception.

Abstract:As a kind of imaging radars, synthetic aperture radar (SAR) improves its resolution by means of moving and emitting pulse repetitiously. The issues about target detection of SAR are often a 憄ost-process?of the SAR imaging. A method for coastline extraction in the state of non-imaging based on analyzing the typical algorithms of SAR imaging and target detection is presented in this paper. Experimental results indicate the validity of the algorithm for coastline extraction. The algorithms are simple, able to recurrent, and easy for real-time processing and hardware implementation.

Abstract:Multi-Agent system (MAS) theory has raised more and more attention from researchers and is experiencing a rapid development in recent years. Many methods based on MAS are emerged and proved successful in solving certain problems, and the AER (Agent-environment-rules) model is one of them used in solving constraint satisfaction problems (CSPs). But the statistic strategy for Agents constrains its ability in problem solving. To tackle this problem, simulated annealing (SA) is introduced to provide Agents with more active and effective strategies. Thus, the application of MAS and SA is successfully combined to form an effective model, SAAER (simulated annealing based AER) model, for solving the CSPs. Results from experiments on the classical CSPs, such as N-queen and coloring problems, show that SAAER model can solve the CSPs at a more effective and stable level. For a large-scale N-queen problem, when N=10000, a precise solution can be obtained in about 200 seconds.

Abstract:Accurate monitoring for the link bandwidth usage of network is important to a variety of network applications. In this paper, a monitoring model on the bandwidth usage of a given set of links is first proposed so as to minimize the overhead imposed by the monitoring procedure on the underlying network. Secondly it is proved that the problem of finding the monitoring model with a minimum overhead is NP-complete. Finally the model is extended by exploiting the flow constraints to further reduce the overhead for monitoring the link bandwidth usage.

Abstract:TCAM (ternary content addressable memory) is a popular device for fast routing lookup. The advantages of TCAM are high lookup speed and simple operation. However, TCAM still has three explicit disadvantages: high cost, high power consumption and complex update. For load balancing and policy routing, routers have to hold considerable routes with multi next hops. This paper proposes a fast IP lookup scheme that is based on TCAM and supports routing lookup for multi next hops. With two index tables, the scheme can store and retrieve the routes with multi next hops. To improve the TCAM update, a fast update algorithm—N-subspace algorithm that can approximately reach the O(1) complexity for current Internet routing tables is also proposed. To decrease cost and power consumption, an efficient routing compaction method is also applied, which is based on the Trie structure and can reduce 20% routes for Internet routing tables. Also, the scheme can scale to IPv6 easily.

Abstract:Rerouting is one of the main schemes used in anonymous communication systems. In some typical anonymous communication systems, data packets pass through a numbers of proxies, and then to the end receiver. So the real initiator could be concealed. However, most rerouting schemes used in some prototype systems are random schemes, which choose the forward proxy randomly among all the proxies in a system. Random rerouting scheme requires every proxy to know some information of all the proxies in the system. With systems expanding, the number of proxies in the system increases, which makes the cost for management higher. Furthermore, its expanding will increase the delay of rerouting as the distance between some of the proxies increases. The paper proposes a new rerouting scheme—short distance-prior rerouting, which implements short distance-prior forwarding, and every proxy chooses a forwarder in its nearby group. The new scheme is applied in the random probability forward rerouting and definite path length rerouting algorithms. Mathematic analysis and simulation results indicate that the new scheme can keep almost the same anonymity as the typical ones and obviously decrease the delay of forwarding. In the new scheme, each proxy only needs to know the information of proxies in its nearby group, which also gives some support to the research of scalability of anonymous systems.

Abstract:For most peer-to-peer file-swapping applications, sharing is a volunteer action, and peers are not responsible for their irresponsible bartering history. This situation indicates the trust between participants can not be set up simply on the traditional trust mechanism. A reasonable trust construction approach comes from the social network analysis, in which trust relations between individuals are set up upon recommendations of other individuals. Current p2p trust model could not promise the convergence of iteration for trust computation, and takes no consideration for model security problems, such as sybil attack and slandering. This paper presents a novel recommendation-based global trust model and gives a distributed implementation method. Mathematic analyses and simulations show that, compared to the current global trust model, the proposed model is more robust on trust security problems and more complete on iteration for computing peer trust.

Abstract:A key issue in one-way delay measurement is the removal of relative clock offset in the situation of without external clock synchronization mechanisms for the end-to-end hosts. Most researches are based on the assumption that the clock skew retains constant and without clock adjustments and drifts during measurement. But in fact, it is found that end system clock might be subject to gradual or instantaneous clock adjustments and frequency adjustments in operation. In this paper, with the time series segmentation technology, we discuss the detection of clock dynamics in one-way delay measurement. Two algorithms are proposed to estimate the relative clock offset in post facto and on-line mode respectively, while with only unidirectional probe packets. The computational complexity of the post facto algorithm is of order O(N²). Experiments show that these algorithms can provide reasonable clock dynamics detection and informative one-way delay estimation.

Abstract:In this paper, a new scheme called aggregated multipath routing (AMR) is presented. In ad hoc networks, routing has been the most focused area for its nodes?mobility and topology variability. Now most of the on-demand routing protocols for current ad hoc networks build and rely on single route for each data session. It is proved in wireless networks that multipath routing is more effective and efficient than single path routing. So multipath routing protocols have been developed for ad hoc networks recently. Whereas these protocols have not provided a good scheme for the source node to collect enough information, a scheme called aggregated multipath routing is proposed. This scheme saves routing information in the source node, uses it to construct multipath, and sends data through these paths alternatively or simultaneously.

Abstract:This paper presents an in-depth analysis of the DCF (distributed coordination function) access mode of IEEE802.11 protocol. Based on the result of this study, the authors have developed a new self-adaptive wireless LAN MAC (medium access control) algorithm with the name of NSAD (new self-adaptive DCF algorithm). Simulation results show that NSAD is superior to DCF in all characters concerned (e.g. goodput, fairness, and packet drop rate).

Abstract:With an increasing requirement of more flexible real-time applications, e.g. multimedia servers in home networks and real-time database servers, a real-time process scheduler using Worst-Case Execution Time (WCET) is inefficient for optimizing performance. Some soft and firm real-time models have been proposed to deal with this situation. This paper presents a feedback control approach for scheduling processes with imprecise computation, a firm real-time model to produce approximate result of an acceptable quality when the exact result of the desired quality cannot be obtained in time. By introducing feedback control to process scheduling, our approach aims to bind the deadline missing ratio under a varying system workload to reach a tradeoff between the deadline missing ratio and result precision.

Abstract:In order to overcome the problem of irregularity of texture features when using the split-and-merge algorithm to segment texture images, the split-and-expand algorithm, a new quadtree-based texture segmentation approach, is presented in this paper. The initial and final regions to be segmented are determined by supervisedly classifying the texture samples of the different regions to be evaluated, and the precision of classification is treated as the weights of the texture features in the corresponding evaluated regions. Then the operation of spliting or expanding is performed according to whether the properties of consistency are satisfied or not. The method can effectively deal with the problem of inconsistent reliability of texture property in different evaluated regions, and the process of expansion can improve the precision of segmentation and avoid the instability of texture features in smaller regions. The results show that the split-and-expand algorithm can effectively segment texture images, and its precision of classification is superior to that of the split-and-merge algorithm.