scholarly journals Optimal routing in a problem with constraints and cost functions depending on the task list

2021 ◽  
Vol 1864 (1) ◽  
pp. 012050
Author(s):  
A. A. Chentsov ◽  
A. G. Chentsov ◽  
A. N. Sesekin
2011 ◽  
Vol 8 (1) ◽  
pp. 346163
Author(s):  
Jiří Trdlička ◽  
Zdeněk Hanzálek

This work proposes a novel in-network distributed algorithm for real-time energy optimal routing in ad hoc and sensor networks for systems with linear cost functions and constant communication delays. The routing problem is described as a minimum-cost multicommodity network flow problem by linear programming and modified by network replication to a real-time aware form. Based on the convex programming theory we use dual decomposition to derive the distributed algorithm. Thanks to the exact mathematical derivation, the algorithm computes the energy optimal real-time routing. It uses only peer-to-peer communication between neighboring nodes and does not need any central node or knowledge about the whole network structure. Each node knows only the produced and collected data flow and the costs of its outgoing communication links. According to our knowledge, this work is the first, which solves the real-time routing problem with linear cost functions and constant communication delays, using the dual decomposition.


1988 ◽  
Author(s):  
Wei K. Tsai ◽  
G. Huang ◽  
John K. Antonio ◽  
Wei-T. Tsai

2017 ◽  
Author(s):  
Sveinn Vidar Gudmundsson ◽  
Rico Merkert ◽  
Renato Redondi
Keyword(s):  

Author(s):  
Kristofer Odolinski ◽  
Phill Wheat
Keyword(s):  

2021 ◽  
Vol 11 (9) ◽  
pp. 4280
Author(s):  
Iurii Katser ◽  
Viacheslav Kozitsin ◽  
Victor Lobachev ◽  
Ivan Maksimov

Offline changepoint detection (CPD) algorithms are used for signal segmentation in an optimal way. Generally, these algorithms are based on the assumption that signal’s changed statistical properties are known, and the appropriate models (metrics, cost functions) for changepoint detection are used. Otherwise, the process of proper model selection can become laborious and time-consuming with uncertain results. Although an ensemble approach is well known for increasing the robustness of the individual algorithms and dealing with mentioned challenges, it is weakly formalized and much less highlighted for CPD problems than for outlier detection or classification problems. This paper proposes an unsupervised CPD ensemble (CPDE) procedure with the pseudocode of the particular proposed ensemble algorithms and the link to their Python realization. The approach’s novelty is in aggregating several cost functions before the changepoint search procedure running during the offline analysis. The numerical experiment showed that the proposed CPDE outperforms non-ensemble CPD procedures. Additionally, we focused on analyzing common CPD algorithms, scaling, and aggregation functions, comparing them during the numerical experiment. The results were obtained on the two anomaly benchmarks that contain industrial faults and failures—Tennessee Eastman Process (TEP) and Skoltech Anomaly Benchmark (SKAB). One of the possible applications of our research is the estimation of the failure time for fault identification and isolation problems of the technical diagnostics.


2019 ◽  
Vol 13 (1) ◽  
pp. 289-300 ◽  
Author(s):  
Subrata Dutta ◽  
Mohammad S. Obaidat ◽  
Keshav Dahal ◽  
Debasis Giri ◽  
Sarmistha Neogy

2021 ◽  
Vol 11 (9) ◽  
pp. 4064
Author(s):  
Muktar Hussaini ◽  
Muhammad Ali Naeem ◽  
Byung-Seo Kim

Named data networking (NDN) is designed as a clean-slate Internet architecture to replace the current IP Internet architecture. The named data networking was proposed to offer vast advantages, especially with the advent of new content distributions in IoT, 5G and vehicular networking. However, the architecture is still facing challenges for managing content producer mobility. Despite the efforts of many researchers that curtailed the high handoff latency and signaling overhead, there are still some prominent challenges, such as non-optimal routing path, long delay for data delivery and unnecessary interest packet losses. This paper proposed a solution to minimize unnecessary interest packet losses, delay and provide data path optimization when the mobile producer relocates by using mobility update, broadcasting and best route strategies. The proposed solution is implemented, evaluated and benchmarked with an existing Kite solution. The performance analysis result revealed that our proposed Optimal Producer Mobility Support Solution (OPMSS) minimizes the number of unnecessary interest packets lost on average by 30%, and an average delay of 25% to 30%, with almost equal and acceptable signaling overhead costs. Furthermore, it provides a better data packet delivery route than the Kite solution.


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