{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,5]],"date-time":"2026-01-05T18:28:31Z","timestamp":1767637711021,"version":"3.48.0"},"reference-count":34,"publisher":"Maximum Academic Press","license":[{"start":{"date-parts":[[2019,7,22]],"date-time":"2019-07-22T00:00:00Z","timestamp":1563753600000},"content-version":"unspecified","delay-in-days":202,"URL":"https:\/\/www.cambridge.org\/core\/terms"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["The Knowledge Engineering Review"],"published-print":{"date-parts":[[2019]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>An increase in volumes of data and a shift towards live data enabled a stronger focus on resource-intensive tasks which run continuously over long periods. A Grid has potential to offer the required resources for these tasks, while considering a fair and balanced allocation of resources among multiple client agents. Taking this into account, a Grid might be unwilling to allocate its resources for long time, leading to task interruptions. This problem becomes even more serious if an interruption of one task may lead to the interruption of dependent tasks. Here, we discuss a new strategy for resource re-allocation which is utilized by a client with the aim to prevent too long interruptions by re-allocating resources between its own tasks. Those re-allocations are suggested by a client agent, but only a Grid can re-allocate resources if agreed. Our strategy was tested under the different Grid settings, accounting for the adjusted coefficients, and demonstrated noticeable improvements in client utilities as compared to when it is not considered. Our experiment was also extended to tests with environmental modelling and realistic Grid resource simulation, grounded in real-life Grid studies. These tests have also shown a useful application of our strategy.<\/jats:p>","DOI":"10.1017\/s0269888919000067","type":"journal-article","created":{"date-parts":[[2019,7,22]],"date-time":"2019-07-22T05:59:04Z","timestamp":1563775144000},"source":"Crossref","is-referenced-by-count":0,"title":["Time-sensitive resource re-allocation strategy for interdependent continuous tasks"],"prefix":"10.48130","volume":"34","author":[{"given":"Valeriia","family":"Haberland","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Simon","family":"Miles","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Michael","family":"Luck","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"27968","published-online":{"date-parts":[[2019,7,22]]},"reference":[{"key":"S0269888919000067_ref32","doi-asserted-by":"publisher","DOI":"10.1016\/j.csi.2006.03.003"},{"key":"S0269888919000067_ref31","doi-asserted-by":"publisher","DOI":"10.1017\/S0269888900008122"},{"key":"S0269888919000067_ref29","doi-asserted-by":"publisher","DOI":"10.1145\/141484.130333"},{"key":"S0269888919000067_ref26","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-540-30501-9_75"},{"key":"S0269888919000067_ref25","unstructured":"Motwani, R. , Widom, J. , Arasu, A. , Babcock, B. , Babu, S. , Datar, M. , Manku, G. , Olston, C. , Rosenstein, J. & Varma, R. 2003. Query Processing, Resource Management, and Approximation in a Data Stream Management System. In The 1st Biennial Conference on Innovative Data Systems Research, 245\u2013256."},{"key":"S0269888919000067_ref33","doi-asserted-by":"publisher","DOI":"10.1109\/71.595579"},{"key":"S0269888919000067_ref23","first-page":"130","article-title":"From Sensor Data Streams to Linked Streaming Data: a survey of main approaches","volume":"7","author":"Llanes","year":"2016","journal-title":"Journal of Information and Data Management"},{"key":"S0269888919000067_ref8","unstructured":"Ghanem, M. , Guo, Y. , Hassard, J. , Osmond, M. & Richards, M. 2004. Sensor Grids for Air Pollution Monitoring. In The 3rd UK e-Science All Hands Meeting."},{"key":"S0269888919000067_ref9","unstructured":"Haberland, V. 2015. Strategies for the Execution of Long-Term Continuous and Simultaneous Tasks in Grids.PhD thesis NMS. King\u2019s College London."},{"key":"S0269888919000067_ref15","unstructured":"Jin, H. , He, Y. , Wen, W. & Liu, H. 2005. A run-time scheduling policy for dependent tasks in grid computing systems. In The 6th International Conference on Parallel and Distributed Computing, Applications and Technologies, 521\u2013523."},{"key":"S0269888919000067_ref10","unstructured":"Haberland, V. , Miles, S. and Luck, M. 2014. Negotiation to Execute Continuous Long-Term Tasks. In The 21st European Conference on Artificial Intelligence, T. Schaub et al. (eds.) Vol. 263. Frontiers in Artificial Intelligence and Applications, 1019\u20131020."},{"key":"S0269888919000067_ref34","unstructured":"Zhao, H. & Sakellariou, R. 2004. A low-cost rescheduling policy for dependent tasks on grid computing systems. 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