The weapon-target assignment (WTA) problem is a fundamental problem arising in defense-related applications of operations research. The WTA problem can be formulated as a nonlinear integer programming problem and is k...
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The weapon-target assignment (WTA) problem is a fundamental problem arising in defense-related applications of operations research. The WTA problem can be formulated as a nonlinear integer programming problem and is known to be NP-complete. We present firstly a technique founded on the use weapon cell, which enables one-to-many mapping about weapon-target to become one-to-one mapping. Next, we introduce a framework of solving the WTA problem. Based on this framework, an approximation algorithm that is grounded on the rules about weapon cells and targets is proposed. Finally, the simulative results show that the proposed algorithm indeed is very efficient.
One fundamental issue in application of wireless sensor networks is to provide proper coverage of their deployment regions, which answers the questions about the quality of service (surveillance or monitoring) that ca...
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ISBN:
(纸本)9780769532585
One fundamental issue in application of wireless sensor networks is to provide proper coverage of their deployment regions, which answers the questions about the quality of service (surveillance or monitoring) that can be provided by a sensor network. In this paper, we consider the point-coverage problem where a given set of n points requires to be covered in the two-dimension (such as monitoring leakage of hazardous gaseous materials at ventilation points or observing the fixed location important targets). Our objective is to place the minimal number sensors such that coverage points in the field can be covered by at least k sensors. By combining computational geometry and combinatorics techniques, we investigate the issue from a different angle, demonstrate an important relationship between coverage points and sensors, and develop an efficient algorithm for 1-coverage problem. Finally, we indicate our approach can easily solve k-coverage problem based on 1-coverage.
This paper presents a search algorithm called probabilistic search team (PST). In PST, all nodes advertise their resource sharing information, maintain and broadcast the information based on DDBF (distributed discardi...
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This paper presents a search algorithm called probabilistic search team (PST). In PST, all nodes advertise their resource sharing information, maintain and broadcast the information based on DDBF (distributed discarding bloom filter), which discards some information when transmitted to their neighbors. During the search process, PST extends the concept of walker in RW to search team. PST realizes collaborative and parallel search of multiple search teams by aggregating the resource information obtained in search process. Experimental results show that PST achieves a good tradeoff between performance and overhead.
As the large-scale data on molecular interaction available increases, the study on biological networks has ignited more and more attention. As the execution level of cellular functions, the structural composition of m...
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As the large-scale data on molecular interaction available increases, the study on biological networks has ignited more and more attention. As the execution level of cellular functions, the structural composition of metabolic networks not only reflects the execution of cellular functions step by step, but also influences the pathway analysis of metabolic engineering. Hence, as a key step, a sound decomposition of global metabolic networks is not only significant for further exploring the structure and function of genome-scale biological networks, but also necessary for favorably developing the pathway analysis of metabolic engineering. Having reviewed the fruitful study of the macro-structure and topological characteristics, and analyzed some available decomposition approaches, this paper concludes that the lack of reasonable and purposeful evaluation criterions is one urgent problem in the present study of metabolic network decomposition. Besides, the future trend is to develop more effective decomposition models with more information and by more advanced approaches, as well as expanding the application range of network decomposition.
This paper proposes an optimistic data consistency method according to the question about data dependence in data consistency. In the method, data object is partitioned into data blocks by fixed size as the basic unit...
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This paper proposes an optimistic data consistency method according to the question about data dependence in data consistency. In the method, data object is partitioned into data blocks by fixed size as the basic unit of data management. Updates are compressed by Bloom filter technique and propagated in double-path. Negotiation algorithms detect and reconcile update conflicts, and dynamic data management algorithms accommodate dynamic data processing. The results of the performance evaluation show that it is an efficient method to achieve consistency, good dynamic property, and strong robustness when choosing the size of data block appropriately. At the same time, a feasible way is put forward on how to choose appropriate data block size.
The features of simple description, small updates item and weak dependence are the main characteristics of updates of key-attributes in P2P systems. Accordingly, an optimistic data consistency maintenance method based...
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The features of simple description, small updates item and weak dependence are the main characteristics of updates of key-attributes in P2P systems. Accordingly, an optimistic data consistency maintenance method based on key-attributes is proposed. In the method, the update of key-attributes is separated from user update requests. Key-Updates are propagated by latency-overlay update propagation model, that is, updates are always propagated to the nodes having maximum or minimum latency, and assured and uncertain propagation paths of updates are all taken into account. Based on classifying key-update conflicts, a double-level reconciling mechanism including buffer preprocessing and update-log processing is applied to detect and reconcile conflicts, and then conflicts are solved by policies as last-writer-win and divide-and-rule. Lastly, update-log management method and maintenance method brought by node failure and network partitioning are discussed for the above is deployed based on the information storied in update-log. Delaying key-attributes updates cannot occur by the optimistic disposal method, and then it cannot depress efficiency of resource location based on key-attributes, which adapts well to P2P systems for Internet. The simulation results show that it is an effective optimistic data consistency maintenance method, achieving good consistency overhead, resource location and resource access overhead, and having strong robustness.
Nowadays, weakly hard real-time is attracted in the research of real-time system. Existing weakly hard real-time scheduling algorithms cannot guarantee the meeting ratio of executing sequence of which the length is la...
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Nowadays, weakly hard real-time is attracted in the research of real-time system. Existing weakly hard real-time scheduling algorithms cannot guarantee the meeting ratio of executing sequence of which the length is larger than fixed window-size. Therefore, this paper, based on the (m, p) constraint, proposes an algorithm which is named as CDBS (cut-down based scheduling). Since the discrimination of the satisfiability of (m, p) constraint needs to go over the whole executing sequence of the task, it's very difficult and infeasible. For this reason, this paper brings an efficient algorithm of cutting down the sequence, proves the correctness of the algorithm. We use proper data structures so that the complexity of judgment is not relevant to the length of sequence. Experiments show the efficiency. Furthermore, we compare CDBS with other classical algorithms, such as EDF, DBP, DWCS, and the results show its competence.
Due to the characteristics of stream applications and the insufficiency of conventional processors when running stream programs, stream processors which support data-level parallelism become the research hotspot. This...
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Due to the characteristics of stream applications and the insufficiency of conventional processors when running stream programs, stream processors which support data-level parallelism become the research hotspot. This paper presents two means, stream partition (SP) and stream compression (SC), to optimize streams on Imagine. The results of simulation show that SP and SC can make stream applications take full advantage of the parallel clusters, pipelines and three-level memory hierarchy of the Imagine processor, and then reduce the execution time of stream programs.
Recent studies on network traffic have shown that self-similar is very popular, and the character will not be changed during buffering, switching and transmitting. The character self-similar must be considered in netw...
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Recent studies on network traffic have shown that self-similar is very popular, and the character will not be changed during buffering, switching and transmitting. The character self-similar must be considered in network traffic prediction. This paper analyzed and summarized the research results of self-similar network traffic prediction from the fields of self-similar modeling, parameter computing and performance prediction. An equivalent bandwidth algorithm of self-similar traffic prediction based on measurement was put forward. Our analysis has shown that the algorithm can effectively reduce computing and realizing complexities.
Searching in large-scale unstructured peer-to-peer networks is challenging due to the lack of effective hint information to guide queries. In this paper, we propose POP, a parallel, cOllaborative and Probabilistic sea...
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