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Message delay and DisCSP search algorithms
 ANN MATH ARTIF INTELL (2006 ) 46 : 415–439
, 2006
"... Distributed constraint satisfaction problems (DisCSPs) are composed of agents, each holding its own variables, that are connected by constraints to variables of other agents. Due to the distributed nature of the problem, message delay can have unexpected effects on the behavior of distributed searc ..."
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Cited by 32 (18 self)
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Distributed constraint satisfaction problems (DisCSPs) are composed of agents, each holding its own variables, that are connected by constraints to variables of other agents. Due to the distributed nature of the problem, message delay can have unexpected effects on the behavior of distributed search algorithms on DisCSPs. This has been recently shown in experimental studies of asynchronous backtracking algorithms (Bejar et al., Artif. Intell., 161:117–148, 2005; Silaghi and Faltings, Artif. Intell., 161:25–54, 2005). To evaluate the impact of message delay on the run of DisCSP search algorithms, a model for distributed performance measures is presented. The model counts the number of non concurrent constraints checks, to arrive at a solution, as a non concurrent measure of distributed computation. A simpler version measures distributed computation cost by the nonconcurrent number of steps of computation. An algorithm for computing these distributed measures of computational effort is described. The realization of the model for measuring performance of distributed search algorithms is a simulator which includes the cost of message delays. Two families of distributed search algorithms on DisCSPs are investigated. Algorithms that run a single search process, and multiple search processes algorithms. The two families of algorithms are described and associated with existing algorithms. The performance of three representative algorithms of these two families is measured on randomly generated instances of DisCSPs with delayed messages. The delay of messages is found to have a strong negative effect on single search process algorithms, whether synchronous or asynchronous. Multi
Asynchronous Forwardchecking for DisCSPs
, 2007
"... A new search algorithm for solving distributed constraint satisfaction problems (DisCSPs) is presented. Agents assign variables sequentially, but perform forward checking asynchronously. The asynchronous forwardchecking algorithm (AFC) is a distributed search algorithm that keeps one consistent par ..."
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Cited by 21 (3 self)
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A new search algorithm for solving distributed constraint satisfaction problems (DisCSPs) is presented. Agents assign variables sequentially, but perform forward checking asynchronously. The asynchronous forwardchecking algorithm (AFC) is a distributed search algorithm that keeps one consistent partial assignment at all times. Forward checking is performed by sending copies of the partial assignment to all unassigned agents concurrently. The algorithm is described in detail and its correctness proven. The sequential assignment method of AFC leads naturally to dynamic ordering of agents during search. Several ordering heuristics are presented. The three best heuristics are evaluated and shown to improve the performance of AFC with static order by a large factor. An experimental comparison of AFC to asynchronous backtracking (ABT) on randomly generated DisCSPs is also presented. AFC with ordering heuristics outperforms ABT by a large factor on the harder instances of random DisCSPs. These results hold for two measures of performance: number of nonconcurrent constraints checks and number of messages sent.
Concurrent search for distributed CSPs
 Artificial Intelligence
, 2006
"... A distributed concurrent search algorithm for distributed constraint satisfaction problems (DisCSPs) is presented. Concurrent search algorithms are composed of multiple search processes (SPs) that operate concurrently and scan nonintersecting parts of the global search space. Each SP is represente ..."
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Cited by 10 (4 self)
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A distributed concurrent search algorithm for distributed constraint satisfaction problems (DisCSPs) is presented. Concurrent search algorithms are composed of multiple search processes (SPs) that operate concurrently and scan nonintersecting parts of the global search space. Each SP is represented by a unique data structure, containing a current partial assignment (CPA), that is circulated among the different agents. Search processes are generated dynamically, started by the initializing agent, and by any number of agents during search. In the proposed, ConcDB, algorithm, all search processes perform dynamic backtracking. As a consequence of backjumping, a search space can be found unsolvable by a different search process. This enhances the efficiency of the ConcDB algorithm. Concurrent Dynamic Backtracking is an asynchronous distributed algorithm and is shown to be faster than former algorithms for solving DisCSPs. Experimental evaluation of ConcDB, on randomly generated DisCSPs demonstrates that the network load of ConcDB is similar to the network load of synchronous backtracking and is much lower than that of asynchronous backtracking. The advantage of Concurrent Search is more pronounced in the presence of imperfect communication, when messages are randomly delayed. Key Words: Constraints Satisfaction, Search, Distributed AI. 1.
Secure discsp protocols  from centralized towards distributed solutions
 in DCR05 Workshop
, 2005
"... Abstract. We present new protocols for secure distributed constraint satisfaction problems (DisCSPs). The presented protocols are the first to enable an oblivious use of advanced search techniques heuristics. The first protocol is a centralized protocol, where two of the agents collect ‘encrypted’ d ..."
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Cited by 7 (0 self)
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Abstract. We present new protocols for secure distributed constraint satisfaction problems (DisCSPs). The presented protocols are the first to enable an oblivious use of advanced search techniques heuristics. The first protocol is a centralized protocol, where two of the agents collect ‘encrypted’ data from all other parties, and obliviously perform a search algorithm. Our protocol improves on the previous solution of [YKH05] in several ways: It does not require introducing new agents into the protocol; it enables the use of nontrivial search techniques such as backjumping and ordering heuristics of variables and values; and, it completely eliminates information leakage to all agents. Our second protocol makes the first steps toward a feasible distributed secured protocol for solving DisCSPs. Our protocol enables agents to concurrently perform non sequential (asynchronous) algorithms. It forms an alternative network, whose nodes are small groups (e.g. pairs) of agents, that is generated from the original DisCSP. Each node group obliviously performs the roles of all its members in the search algorithm. We also identify the communication pattern of the protocol as a possible leakage source, and suggest how to eliminate this leakage. Finally, we discuss a hybrid solution that combines the centralized and distributed protocols and reduces the total communication cost. 1
Message delay and asynchronous DisCSP search
, 2006
"... Distributed constraint satisfaction problems (DisCSPs) are composed of agents, each holding its own variables, that are connected by constraints to variables of other agents. Due to the distributed nature of the problem, message delay can have unexpected effects on the behavior of distributed searc ..."
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Cited by 5 (4 self)
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Distributed constraint satisfaction problems (DisCSPs) are composed of agents, each holding its own variables, that are connected by constraints to variables of other agents. Due to the distributed nature of the problem, message delay can have unexpected effects on the behavior of distributed search algorithms on DisCSPs. This has been shown in experimental studies of asynchronous backtracking algorithms [1, 9]. To evaluate the impact of message delay on the run of DisCSP search algorithms, a model for distributed performance measures is presented. The model counts the number of non concurrent constraints checks, to arrive at a solution, as a non concurrent measure of distributed computation. A simpler version measures distributed computation cost by the number of nonconcurrent steps of computation. An algorithm for computing these distributed measures of computational effort is described. The realization of the model for measuring performance of distributed search algorithms is a simulator which includes the cost of message delays. The performance of two asynchronous search algorithms is measured on randomly generated instances of DisCSPs with delayed messages. The Asynchronous Weak Commitment (AW C) algorithm and Asynchronous Backtracking (ABT). The intrinsic reordering process of AW C dictates a need for a more complex count of nonconcurrent steps of computation. The improved counting algorithm is also needed for Dynamic ordered ABT. The delay of messages is found to have a strong negative effect on AW C and a smaller effect on dynamically ordered ABT.
PROGRAMME DOCTORAL EN INFORMATIQUE, COMMUNICATIONS ET INFORMATION ÉCOLE POLYTECHNIQUE FÉDÉRALE DE LAUSANNE POUR L'OBTENTION DU GRADE DE DOCTEUR ÈS SCIENCES PAR
"... acceptée sur proposition du jury: Prof. K. Aberer, président du jury Prof. B. Faltings, directeur de thèse Prof. J.P. Hubaux, rapporteur Dr J.A. Rodriguez Aguilar, rapporteur ..."
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acceptée sur proposition du jury: Prof. K. Aberer, président du jury Prof. B. Faltings, directeur de thèse Prof. J.P. Hubaux, rapporteur Dr J.A. Rodriguez Aguilar, rapporteur
— Ludwig van Beethoven (1770–1827) Acknowledgements
"... programme doctoral en Informatique et Communications ..."
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"... A distributed concurrent search algorithm for distributed constraint satisfaction problems (DisCSPs) is presented. Concurrent search algorithms are composed of multiple search processes (SPs) that operate concurrently and scan nonintersecting parts of the global search space. Each SP is represented ..."
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A distributed concurrent search algorithm for distributed constraint satisfaction problems (DisCSPs) is presented. Concurrent search algorithms are composed of multiple search processes (SPs) that operate concurrently and scan nonintersecting parts of the global search space. Each SP is represented by a unique data structure, containing a current partial assignment (CPA), that is circulated among the different agents. Search processes are generated dynamically, started by the initializing agent, and by any number of agents during search. In the proposed, ConcDB, algorithm, all search processes perform dynamic backtracking. As a consequence of backjumping, a search space can be found unsolvable by a different search process. This enhances the efficiency of the ConcDB algorithm. Concurrent Dynamic Backtracking is an asynchronous distributed algorithm and is shown to be faster than former algorithms for solving DisCSPs. Experimental evaluation of ConcDB, on randomly generated DisCSPs demonstrates that the network load of ConcDB is similar to the network load of synchronous backtracking and is much lower than that of asynchronous backtracking. The advantage of Concurrent Search is more pronounced in the presence of imperfect communication, when messages are randomly delayed.
CP04 Tutorial: Distributed Constraints Satisfaction Algorithms, Performance, Communication ⋆
"... Abstract. Distributed constraints satisfaction problems (DisCSPs) have been studied for over a decade. The first distributed search algorithm was asynchronous backtracking, which is still the most studied. In the last few years, several new families of distributed search algorithms have been investi ..."
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Abstract. Distributed constraints satisfaction problems (DisCSPs) have been studied for over a decade. The first distributed search algorithm was asynchronous backtracking, which is still the most studied. In the last few years, several new families of distributed search algorithms have been investigated and comparative experimental studies are encouraging. A natural extension to distributed constraints satisfaction is distributed constraints optimization. Stochastic search algorithms for solving DisCSP s, such as Distributed Breakout, have appeared a few years ago. Distributed stochastic search algorithms are naturally suitable for solving distributed optimization. In contrast, asynchronous search algorithms for distributed optimization have been proposed in recent years. Due to the distributed nature of the problem, message delay can have unexpected effects on the behavior of algorithms on DisCSP s. This has been shown in an experimental study that induced random delays on messages sent among agents. In order to study the impact of message delays on DisCSP search, a model of delays in terms of concurrent performance measures is needed. Within such a model, the behavior of families of search algorithms in the presence of delays is varied and interesting. An important feature of the distribution of the problem among agents is their ability to maintain some privacy. Agents may not want to share their values with other agents, and they may wish to keep constraints as private as possible. Some recent work has resulted in versions of asynchronous backtracking that maintain both privacy of values and privacy of constraints. Other investigations of privacy in DisCSP s focused on the analysis of information gain by studying a welldefined problem, that of scheduling meetings of agents. 1
Reducing Redundant Messages in the Asynchronous Backtracking Algorithm
"... Abstract. We show how the Asynchronous Backtracking Algorithm, a well known distributed constraint satisfaction algorithm, produces unnecessary messages. Our new optimized algorithm reduces the number of messages by implementing message management mechanism. Tests show our algorithm significantly re ..."
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Abstract. We show how the Asynchronous Backtracking Algorithm, a well known distributed constraint satisfaction algorithm, produces unnecessary messages. Our new optimized algorithm reduces the number of messages by implementing message management mechanism. Tests show our algorithm significantly reduces the total number of messages sent and drastically reduces the number of cycles used when solving instances of the graph coloring problem. 1