ORCID Profile
0000-0001-9194-010X
Current Organisations
Karlstad University
,
Queen's University Belfast
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In Research Link Australia (RLA), "Research Topics" refer to ANZSRC FOR and SEO codes. These topics are either sourced from ANZSRC FOR and SEO codes listed in researchers' related grants or generated by a large language model (LLM) based on their publications.
Analysis of Algorithms and Complexity | Distributed Computing | Distributed and Grid Systems | Stochastic Analysis and Modelling |
Expanding Knowledge in the Information and Computing Sciences | Application Tools and System Utilities | Management of Greenhouse Gas Emissions from Information and Communication Services
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 09-2023
Publisher: IEEE
Date: 12-2009
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 04-2022
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2022
Publisher: Elsevier BV
Date: 08-2011
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2022
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 10-2022
Publisher: Elsevier BV
Date: 02-2007
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 05-2021
Publisher: Elsevier BV
Date: 08-2011
Publisher: World Scientific Pub Co Pte Lt
Date: 02-2012
DOI: 10.1142/S0129054112400229
Abstract: A large number of optimization problems have been identified as computationally challenging and/or intractable to solve within a reasonable amount of time. Due to the NP-hard nature of these problems, in practice, heuristics account for the majority of existing algorithms. Metaheuristics are one very popular type of heuristics used for many of these optimization problems. In this paper, we present a novel parallel-metaheuristic framework, which effectively enables to devise parallel metaheuristics, particularly with heterogeneous metaheuristics. The core component of the proposed framework is its harmony-search-based coordinator. Harmony search is a recent breed of metaheuristic that mimics the improvisation process of musicians. The coordinator facilitates heterogeneous metaheuristics (forming a parallel metaheuristic) to escape local optima. Specifically, best solutions generated by these worker metaheuristics are maintained in the harmony memory of the coordinator, and they are used to form new-possibly better-harmonies (solutions) before actual solution sharing between workers occurs hence, their solutions are harmonized with each other. For the applicability validation and the performance evaluation, we have implemented a parallel hybrid metaheuristic using the framework for the task scheduling problem on multiprocessor computing systems (e.g., computer clusters). Experimental results verify that the proposed framework is a compelling approach to parallelize heterogeneous metaheuristics.
Publisher: Wiley
Date: 03-12-2008
DOI: 10.1002/WCM.582
Publisher: IEEE
Date: 03-2008
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 10-2021
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2018
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 31-05-2023
DOI: 10.36227/TECHRXIV.20490093
Abstract: To automate network operations and deployment of compute services, intent-driven service management (IDSM) is essential. It enables network users to express their service requirements in a declarative manner as em intents /em . To fulfill the intents, closed control-loop operations carry out required configurations and deployments without human intervention. Despite the fact that intents are fulfilled automatically, conflicts may arise between user’s and service provider’s intents due to limited resources availability. This triggers IDSM system to initialize an intent negotiation process among conflicting actors. Intent negotiation involves generating one or more alternate intents based on the current state of the underlying physical/virtual resources, which are then presented to the intent creator for acceptance or rejection. In this way, the quality of services (QoS) can be improved significantly by maximizing the acceptance rate of service requests in the scenario of limited resources. However, intent negotiation systems are still in their infancy. The available solutions are platform dependent which poses various challenges in their adoption to erse platforms. The main focus of this work is to draft and evaluate a comprehensive and generic intent negotiation framework which can be used to develop intent ne- gotiation solutions for erse IDSM platforms. In this work, we have identified and defined various processes that are necessary for intent negotiation. Furthermore, a generic intent negotiation framework is presented representing interactions among the identified processes, while conflicting actors engage in the intent negotiation. The results demonstrated that the proposed intent negotiation framework increases the intent acceptance rate by up to 38% with processing overheads less than 10%.
Publisher: IEEE
Date: 05-2012
Publisher: IEEE
Date: 2009
Publisher: Elsevier BV
Date: 06-2013
Publisher: Springer Science and Business Media LLC
Date: 2009
Publisher: Elsevier BV
Date: 05-2018
Publisher: Elsevier BV
Date: 2013
Publisher: Elsevier BV
Date: 04-2007
Publisher: IEEE
Date: 07-11-2022
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 06-2008
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 04-2023
Publisher: Springer International Publishing
Date: 2023
Publisher: IEEE
Date: 05-2012
Publisher: IEEE
Date: 09-2012
DOI: 10.1109/GRID.2012.25
Publisher: Elsevier BV
Date: 10-2012
DOI: 10.1016/J.JBI.2012.03.004
Abstract: Discovering ways to reconstruct reliable Single In idual Haplotypes (SIHs) becomes one of the core issues in the whole-genome research nowadays as previous research showed that haplotypes contain more information than in idual Singular Nucleotide Polymorphisms (SNPs). Although with advances in high-throughput sequencing technologies obtaining sequence information is becoming easier in today's laboratories, obtained sequences from current technologies always contain inevitable sequence errors and missing information. The SIH reconstruction problem can be formulated as bi-partitioning the input SNP fragment matrix into paternal and maternal sections to achieve minimum error correction (MEC) time the problem that is proved to be NP-hard. Several heuristics or greedy algorithms have already been designed and implemented to solve this problem, most of them however (1) do not have the ability to handle data sets with high error rates and/or (2) can only handle binary input matrices. In this study, we introduce a Genetic Algorithm (GA) based method, named GAHap, to reconstruct SIHs with lowest MEC times. GAHap is equipped with a well-designed fitness function to obtain better reconstruction rates. GAHap is also compared with existing methods to show its ability in generating highly reliable solutions.
Publisher: Springer Science and Business Media LLC
Date: 25-03-2017
Publisher: Springer International Publishing
Date: 28-11-2022
Publisher: Springer International Publishing
Date: 28-11-2022
Publisher: Springer International Publishing
Date: 28-11-2022
Publisher: Springer International Publishing
Date: 28-11-2022
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2023
Publisher: Springer International Publishing
Date: 28-11-2022
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 06-2023
Publisher: Springer International Publishing
Date: 28-11-2022
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 09-2020
Publisher: Springer International Publishing
Date: 28-11-2022
Publisher: IEEE
Date: 03-2008
Publisher: IEEE
Date: 03-2008
Publisher: IEEE
Date: 06-06-2023
Publisher: Wiley
Date: 30-12-2023
DOI: 10.1002/CPE.6799
Abstract: Apache Storm is a distributed processing engine that can reliably process unbounded streams of data for real‐time applications. While recent research activities mostly focused on devising a resource allocation and task scheduling algorithm to satisfy high performance or low latency requirements of Storm applications across a distributed and multi‐core system, finding a solution that can optimize the energy consumption of running applications remains an important research question to be further explored. In this article, we present a controlling strategy for CPU throttling that continuously optimize the level of consumed energy of a Storm platform by adjusting the voltage and frequency of the CPU cores while running the assigned tasks under latency constraints defined by the end‐users. The experimental results running over a Storm cluster with 4 physical nodes (total 24 cores) validates the effectiveness of proposed solution when running multiple compute‐intensive operations. In particular, the proposed controller can keep the latency of analytic tasks, in terms of 99th latency percentile, within the quality of service requirement specified by the end‐user while reducing the total energy consumption by 18% on average across the entire Storm platform.
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 23-01-2023
DOI: 10.36227/TECHRXIV.20490093.V2
Abstract: To automate network operations and deployment of compute services, intent-driven service management (IDSM) is essential. It enables network users to express their service requirements in a declarative manner as em intents /em . To fulfill the intents, closed control-loop operations carry out required configurations and deployments without human intervention. Despite the fact that intents are fulfilled automatically, conflicts may arise between user’s and service provider’s intents due to limited resources availability. This triggers IDSM system to initialize an intent negotiation process among conflicting actors. Intent negotiation involves generating one or more alternate intents based on the current state of the underlying physical/virtual resources, which are then presented to the intent creator for acceptance or rejection. In this way, the quality of services (QoS) can be improved significantly by maximizing the acceptance rate of service requests in the scenario of limited resources. However, intent negotiation systems are still in their infancy. The available solutions are platform dependent which poses various challenges in their adoption to erse platforms. The main focus of this work is to draft and evaluate a comprehensive and generic intent negotiation framework which can be used to develop intent ne- gotiation solutions for erse IDSM platforms. In this work, we have identified and defined various processes that are necessary for intent negotiation. Furthermore, a generic intent negotiation framework is presented representing interactions among the identified processes, while conflicting actors engage in the intent negotiation. The results demonstrated that the proposed intent negotiation framework increases the intent acceptance rate by up to 38% with processing overheads less than 10%.
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 31-05-2023
DOI: 10.36227/TECHRXIV.20490093.V3
Abstract: To automate network operations and deployment of compute services, intent-driven service management (IDSM) is essential. It enables network users to express their service requirements in a declarative manner as em intents /em . To fulfill the intents, closed control-loop operations carry out required configurations and deployments without human intervention. Despite the fact that intents are fulfilled automatically, conflicts may arise between user’s and service provider’s intents due to limited resources availability. This triggers IDSM system to initialize an intent negotiation process among conflicting actors. Intent negotiation involves generating one or more alternate intents based on the current state of the underlying physical/virtual resources, which are then presented to the intent creator for acceptance or rejection. In this way, the quality of services (QoS) can be improved significantly by maximizing the acceptance rate of service requests in the scenario of limited resources. However, intent negotiation systems are still in their infancy. The available solutions are platform dependent which poses various challenges in their adoption to erse platforms. The main focus of this work is to draft and evaluate a comprehensive and generic intent negotiation framework which can be used to develop intent ne- gotiation solutions for erse IDSM platforms. In this work, we have identified and defined various processes that are necessary for intent negotiation. Furthermore, a generic intent negotiation framework is presented representing interactions among the identified processes, while conflicting actors engage in the intent negotiation. The results demonstrated that the proposed intent negotiation framework increases the intent acceptance rate by up to 38% with processing overheads less than 10%.
Publisher: World Scientific Pub Co Pte Lt
Date: 04-2011
DOI: 10.1142/S0129054111008210
Abstract: This work reviews a number of algorithms to solve the location management problem in mobile networks for both static and dynamic scenarios. In the static mode, results of five algorithms are used to highlight the pros and cons for each algorithm. These results provide new insight into the mobility management problem that can influence the design of future wireless networks. In the dynamic mode in which mobile users' past movement patterns are used in making future paging decisions by the network, the performance of an online location management algorithm is examined under different deployment setups. Performance results of this algorithm show its advantages over the currently implemented and/or proposed static location management systems (including GSM).
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 23-08-2022
DOI: 10.36227/TECHRXIV.20490093.V1
Abstract: To automate network operations and compute ser- vices, intent-driven service management (IDSM) is essential. It enables network users to express their service requirements in a declarative manner as em i /em ntents. To fulfill the intents, closed control-loop operations perform required configurations and deployments without human intervention. Despite the fact that the intents are fulfilled automatically, conflicts may arise between users and service providers due to limited capabilities of service providers and user requirements specified as intents. This triggers IDSM system to initialize an intent negotiation process among conflicting actors. Intent negotiation involves generating one or more alternate intents based on the current state of the underlying physical/virtual resources, which are then presented to the intent creator for acceptance or rejection. In this way, the quality of services (QoS) can be improved significantly by maximizing the acceptance rate of service requests in the scenario of limited resources. However, intent negotiation sub-systems are still in their infancy. The available solutions are platform dependent which pose various challenges in their adoption to erse platforms. The main focus of this work has been to draft a comprehensive and generic intent negotiation framework which can be used across erse IDSM platforms. In this work, we have identified and defined various processes that are necessary for a comprehensive intent negotiation framework. A generic intent negotiation framework is then presented incorporating all the interactions among all the identified processes while conflicting actors engage in the intent negotiation, towards the fulfilment of the given service.
Location: United Kingdom of Great Britain and Northern Ireland
Start Date: 02-2019
End Date: 01-2022
Amount: $425,134.00
Funder: Australian Research Council
View Funded ActivityStart Date: 04-2016
End Date: 12-2019
Amount: $574,932.00
Funder: Australian Research Council
View Funded Activity