Architecture of Computing Systems (Lecture Notes in Computer ...

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184 T. Abdullah et al. % Matchmaking Efficiency 100 80 60 40 20 0 0 1 2 3 4 5 6 Number of Matchmakers (a) Matchmaking Efficiency % Matchmaking Efficiency 50 40 30 20 10 0 0 10 20 30 40 50 60 70 80 90 100 110 Degree of Neighborhood (b) Matchmaking Efficiency Fig. 4. (a) Matchmaking efficiency of centralized and multiple adaptive matchmakers approach. (b) Matchmaking efficiency with varying the degree of neighborhood in completely decentralized (P2P). more matchmaker(s) when needed by an overloaded matchmaker(s). Hence, the matchmaking efficiency remains the same with the increased number of matchmakers. The matchmaking efficiency of completely centralized resource discovery approach is slightly higher than that of multiple adaptive matchmakers approach (Figure 4a). The matchmakers in multiple adaptive matchmakers approach communicate with other matchmakers in order to promote/demote matchmakers and for sharing their access workload with the other matchmakers [12]. Some of the request/offer messages expire during this process. Since, there is no communication or work load sharing with other matchmakers in the completely centralized approach, the maximum matchmaking efficiency of the completely centralized system is slightly higher than that of the multiple adaptive matchmakers system. However, the completely centralized approach is not scalable and can have a single point of failure [12,13]. Figure 4b shows the matchmaking efficiency of the resource discovery approach with varying the degree of neighborhood in a completely decentralized (P2P) ad hoc grid. The matchmaking efficiency initially increases with an increased degree of neighborhood. This seems logical as with an increased degree of neighborhood, the chances for finding a required resource/offer also increase. However, this trend starts decreasing with further increase in the degree of neighborhood due to the increased number of request/offer messages (refer to Figure 3a). The matchmaker agent of each node has to process more messages. The increased processing time results in TTL expiry of request/offer messages and consequently a drop in the matchmaking efficiency. The experiments were repeated for n = 100, 250 and d was varied from d =2, 4, 6, 8, ..., n. Thesame matchmaking pattern as in Figure 4b was observed. An alternative view of the above discussed phenomenon is to consider the average response time. Figure 5a shows the average response time to find a match with varying the degree of neighborhood in a completely decentralized (P2P) ad hoc grid. Inourexperiments,theresponsetimestaysstableupto 50 hops in the P2P case. The response time increases more than proportional
Response Time (milliseconds) 14 12 10 8 6 4 2 Response Time Effect of the Degree of Neighborhood on Resource Discovery 185 0 0 10 20 30 40 50 60 70 80 90 100 110 Degree of Neighborhood (a) Response Time (milliseconds) 30 25 20 15 10 5 Response Time 0 0 1 2 3 4 5 6 Number of Matchmaker Fig. 5. (a) Response time with varying the degree of neighborhood in the completely decentralized (P2P) approach. (b) Response time of centralized and multiple adaptive matchmakers approach. once the number of hops goes beyond 60 (Figure 5a). The over proportional increase in response time is due to the communication overhead incurred with the increased degree of neighborhood in the completely decentralized (P2P) ad hoc gird. We observe an increase in the response time of multiple adaptive matchmakers approach with increased number of matchmakers (Figure 5b). This increase is due to the segmentation of the ad hoc grid and due to increased communication as explained in Section 5. The experiments were also executed under resource intensive and task intensive network conditions. We observed the same trend of the matchmaking efficiency and response time as discussed above. It can be concluded from the above discussion that neither a completely centralized nor a completely decentralized (P2P) is generally a suitable infrastructures for resource discovery in an ad hoc grid. A completely centralized infrastructure is not scalable and can have a single point of failure. On the other hand, a completely decentralized (P2P) infrastructure incurs excessive communication overhead that results in an increased response time and decreased matchmaking efficiency. An intermediate infrastructure having multiple adaptive matchmakers seems most efficient in terms of response time and in finding matches. The intermediate infrastructure with multiple adaptive matchmakers should be preferred whenever possible in the ad hoc grid. 7 Conclusions In this paper, we analyzed the effect of varying the degree of neighborhood on resource discovery in a local ad hoc grid. For this purpose we defined and implemented the degree of neighborhood for participating nodes. Results were obtained for completely centralized, multiple adaptive matchmakers and for completely decentralized resource discovery approaches in an ad hoc grid. Results (b)
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Lecture Notes in Computer Science 5
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Volume Editors Christian Müller-Sc
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General Chair Organization Christia
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Organization IX Hartmut Schmeck Kar
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Keynote Table of Contents HyVM - Hy
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Table of Contents XIII JetBench:AnO
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How to Enhance a Superscalar Proces
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4 J. Mische et al. The Real-time Vi
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Exploiting Inactive Rename Slots fo
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130 M. Kayaalp et al. INSTRUCTION 1
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244 F. Xudong et al. 5 Related Work
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Abdullah, Tariq 174 Alima, Luc Onan
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