| 1. |
- Abdulla, Parosh Aziz, 1961-, et al.
(författare)
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Special Issue on NETYS'2016
- 2019
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Ingår i: Computing. - : Springer Nature. - 0010-485X .- 1436-5057. ; 101:1, s. 1-2
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Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)
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| 2. |
- Alhamazani, Khalid, et al.
(författare)
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An overview of the commercial cloud monitoring tools: research dimensions, design issues, and state-of-the-art
- 2015
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Ingår i: Computing. - : Springer Science and Business Media LLC. - 0010-485X .- 1436-5057. ; 97:4, s. 357-377
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Tidskriftsartikel (refereegranskat)abstract
- Cloud monitoring activity involves dynamically tracking the Quality of Service (QoS) parameters related to virtualized resources (e.g., VM, storage, network, appliances, etc.), the physical resources they share, the applications running on them and data hosted on them. Applications and resources configuration in cloud computing environment is quite challenging considering a large number of heterogeneous cloud resources. Further, considering the fact that at given point of time, there may be need to change cloud resource configuration (number of VMs, types of VMs, number of appliance instances, etc.) for meet application QoS requirements under uncertainties (resource failure, resource overload, workload spike, etc.). Hence, cloud monitoring tools can assist a cloud providers or application developers in: (i) keeping their resources and applications operating at peak efficiency, (ii) detecting variations in resource and application performance, (iii) accounting the service level agreement violations of certain QoS parameters, and (iv) tracking the leave and join operations of cloud resources due to failures and other dynamic configuration changes. In this paper, we identify and discuss the major research dimensions and design issues related to engineering cloud monitoring tools. We further discuss how the aforementioned research dimensions and design issues are handled by current academic research as well as by commercial monitoring tools.
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| 3. |
- AlSkaif, T., et al.
(författare)
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A distributed power sharing framework among households in microgrids : a repeated game approach
- 2016
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Ingår i: Computing. - : Springer. - 0010-485X .- 1436-5057. ; 99:1, s. 23-37
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Tidskriftsartikel (refereegranskat)abstract
- In microgrids, the integration of distributed energy resources (DERs) in the residential sector can improve power reliability, and potentially reduce power demands and carbon emissions. Improving the utilization of renewable energy in households is a critical challenge for DERs. In this regard, renewable power sharing is one of the possible solutions to tackle this problem. Even though this solution has attracted significant attention recently, most of the proposed power sharing frameworks focus more on centralized schemes. In contrast, in this paper, the performance of a proposed distributed power sharing framework is investigated. The problem is formulated as a repeated game between households in a microgrid. In this game, each household decides to cooperate and borrow/lend some amount of renewable power from/to a neighboring household, or to defect and purchase the entire demands from the main grid based on a payoff function. The Nash equilibrium of this game is characterized and the effect of the strategies taken by the households on the system is analyzed. We conduct an extensive evaluation using real demand data from 12 households of different sizes and power consumption profiles in Stockholm. Numerical results indicate that cooperation is beneficial from both an economical and environmental perspective and that households can achieve cost savings up to 20 %.
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| 4. |
- Andersson, Jesper, 1970-, et al.
(författare)
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A conceptual framework for resilience : fundamental definitions, strategies and metrics
- 2021
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Ingår i: Computing. - : Springer. - 0010-485X .- 1436-5057. ; 103, s. 559-588
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Tidskriftsartikel (refereegranskat)abstract
- The resilience system property has become more and more relevant, mainly because of the increasing dependance on a rapidly growing number of software-intensive, complex, socio-technical systems, which are facing uncertainty about changes they are expected to experience during their life-cycle and ways to deal with them. Methodologies for the systematic design and validation of resilience for such systems are thus highly necessary, and require contributions from several different fields. This paper contributes to current resilience research by providing a conceptual framework intended to serve as a common ground for the development of such methodologies. Its main points are: the identification of the main categories of changes a system should face; a clear definition of the different facets of resilience one could want to achieve, expressed in terms of the system dynamics; a mapping of each of these facets to design strategies that are better suited to achieve it; and the corresponding identification of possible metrics that can be used to assess its achievement.
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| 5. |
- Andersson, Jesper, 1970-, et al.
(författare)
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Architecting decentralized control in large-scale self-adaptive systems
- 2023
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Ingår i: Computing. - : Springer. - 0010-485X .- 1436-5057. ; 105, s. 1849-1882
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Tidskriftsartikel (refereegranskat)abstract
- Architecting a self-adaptive system with decentralized control is challenging. Indeed, architects shall consider several different and interdependent design dimensions and devise multiple control loops to coordinate and timely perform the correct adaptations. To support this task, we propose Decor, a reasoning framework for architecting and evaluating decentralized control. Decor provides (i) multi-paradigm modeling support, (ii) a modeling environment for MAPE-K style decentralized control, and (iii) a co-simulation environment for simulating the decentralized control together with the managed system and estimating the quality attributes of interest. We apply the Decor in three case studies: an intelligent transportation system, a smart power grid, and a cloud computing application. The studies demonstrate the framework’s capabilities to support informed architectural decisions on decentralized control and adaptation strategies.
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| 6. |
- Andrejev, Andrej, et al.
(författare)
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Strategies for array data retrieval from a relational back-end based on access patterns
- 2020
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Ingår i: Computing. - : Springer Science and Business Media LLC. - 0010-485X .- 1436-5057. ; 102:5, s. 1139-1158
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Tidskriftsartikel (refereegranskat)abstract
- Multidimensional numeric arrays are often serialized to binary formats for efficient storage and processing. These representations can be stored as binary objects in existing relational database management systems. To minimize data transfer overhead when arrays are large and only parts of arrays are accessed, it is favorable to split these arrays into separately stored chunks. We process queries expressed in an extended graph query language SPARQL, treating arrays as node values and having syntax for specifying array projection, element and range selection operations as part of a query. When a query selects parts of one or more arrays, only the relevant chunks of each array should be retrieved from the relational database. The retrieval is made by automatically generated SQL queries. We evaluate different strategies for partitioning the array content, and for generating the SQL queries that retrieve it on demand. For this purpose, we present a mini-benchmark, featuring a number of typical array access patterns. We draw some actionable conclusions from the performance numbers.
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| 7. |
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| 8. |
- Badidi, Elarbi, et al.
(författare)
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On Personalized Cloud Service Provisioning for Mobile Users Using Adaptive and Context-Aware Service Composition
- 2018
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Ingår i: Computing. - : Springer. - 0010-485X .- 1436-5057. ; 101:4, s. 291-318
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Tidskriftsartikel (refereegranskat)abstract
- Cloud service providers typically compose their services from a number of elementary services, which are developed in- house or built by third-party providers. Personalization of composite services in mobile environments is an interesting and challenging issue to address, given the opportunity to factor-in diverse user preferences and the plethora of mobile devices at use in multiple contexts. This work proposes a framework to address personalization in mobile cloud-service provisioning. Service personalization and adaptation may be considered at different levels, including the user profile, the mobile device in use, the context of the user and the composition specification. The user’s mobile device and external services are typical sources of context information, used in our proposed algorithm to elicit context-aware services. The selection process is guided by quality-of-context (QoC) criteria that combine cloud-service provider requirements and user preferences. Hence, the paper proposes an integrated framework for enhancing personalized mobile cloud-services, based on a composition approach that adapts context information using a common model of service metadata specification.
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| 9. |
- Bhatti, Muhammad Khurram, et al.
(författare)
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Locality-aware task scheduling for homogeneous parallel computing systems
- 2018
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Ingår i: Computing. - : Springer Science and Business Media LLC. - 0010-485X .- 1436-5057. ; 100:6, s. 557-595
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Tidskriftsartikel (refereegranskat)abstract
- In systems with complex many-core cache hierarchy, exploiting data locality can significantly reduce execution time and energy consumption of parallel applications. Locality can be exploited at various hardware and software layers. For instance, by implementing private and shared caches in a multi-level fashion, recent hardware designs are already optimised for locality. However, this would all be useless if the software scheduling does not cast the execution in a manner that promotes locality available in the programs themselves. Since programs for parallel systems consist of tasks executed simultaneously, task scheduling becomes crucial for the performance in multi-level cache architectures. This paper presents a heuristic algorithm for homogeneous multi-core systems called locality-aware task scheduling (LeTS). The LeTS heuristic is a work-conserving algorithm that takes into account both locality and load balancing in order to reduce the execution time of target applications. The working principle of LeTS is based on two distinctive phases, namely; working task group formation phase (WTG-FP) and working task group ordering phase (WTG-OP). The WTG-FP forms groups of tasks in order to capture data reuse across tasks while the WTG-OP determines an optimal order of execution for task groups that minimizes the reuse distance of shared data between tasks. We have performed experiments using randomly generated task graphs by varying three major performance parameters, namely: (1) communication to computation ratio (CCR) between 0.1 and 1.0, (2) application size, i.e., task graphs comprising of 50-, 100-, and 300-tasks per graph, and (3) number of cores with 2-, 4-, 8-, and 16-cores execution scenarios. We have also performed experiments using selected real-world applications. The LeTS heuristic reduces overall execution time of applications by exploiting inter-task data locality. Results show that LeTS outperforms state-of-the-art algorithms in amortizing inter-task communication cost.
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| 10. |
- Cai, Simin, et al.
(författare)
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Data Aggregation Processes : A Survey, A Taxonomy, and Design Guidelines
- 2019
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Ingår i: Computing. - : Springer Science and Business Media LLC. - 0010-485X .- 1436-5057. ; 101:10, s. 1397-1429
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Tidskriftsartikel (refereegranskat)abstract
- Data aggregation processes are essential constituents for data management in modern computer systems, such as decision support systems and Internet of Things (IoT) systems, many with timing constraints. Understanding the common and variable features of data aggregation processes, especially their implications to the timerelated properties, is key to improving the quality of the designed system and reduce design effort. In this paper, we present a survey of data aggregation processes in a variety of application domains from literature.We investigate their common and variable features, which serves as the basis of our previously proposed taxonomy called DAGGTAX. By studying the implications of the DAGGTAX features, we formulate a set of constraints to be satisfied during design, which helps to check the correctness of the specifications and reduce the design space. We also provide a set of design heuristics that could help designers to decide the appropriate mechanisms for achieving the selected features. We apply DAGGTAX on industrial case studies, showing that DAGGTAX not only strengthens the understanding, but also serves as the foundation of a design tool which facilitates the model-driven design of data aggregation processes.
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| 11. |
- Cebrian, Juan M., et al.
(författare)
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Efficient inter-core power and thermal balancing for multicore processors
- 2013
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Ingår i: Computing. - : Springer Science and Business Media LLC. - 0010-485X .- 1436-5057. ; 95:7, s. 537-566
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Tidskriftsartikel (refereegranskat)abstract
- Nowadays the market is dominated by processor architectures that employ multiple cores per chip. These architectures have different behavior depending on the applications running on the processor (parallel, multiprogrammed, sequential), but all happen to meet what is called the power and temperature wall. For future technologies (less than 22 nm) and a fixed die size, it is still uncertain the percentage of processor that can be simultaneously powered on. Power saving and power budget mechanisms can be useful to precisely control the amount of power been dissipated by the processor. After an initial analysis we discover that legacy power saving techniques work properly for matching a power budget in thread-independent and multi-programmed workloads, but not in parallel workloads. When running parallel shared-memory applications sacrificing some performance in a single core (thread) in order to be more energy-efficient can unintentionally delay the rest of cores (threads) due to synchronization points (locks/barriers), having a negative impact on global performance. In order to solve this problem we propose power token balancing (PTB) aimed at accurately matching an external power constraint by balancing the power consumed among the different cores. Experimental results show that PTB matches more accurately a predefined power budget (50 % of the original peak power) than other mechanisms like DVFS. The total energy consumed over the budget is reduced to only 8 % for a 16-core CMP with only a 3 % energy increase (overhead). We also introduce a novel mechanism named "Nitro". Nitro will overclock the core that enters a critical section (delimited by locks) in order to free the lock as soon as possible. Experimental results have shown that Nitro is able to reduce the execution time of lock-intensive applications in more than 4 % by overclocking the frequency by 15 % in selected program phases over a period of time that represents a 22 % of the total execution time. We conclude the work with an analysis of the thermal effects of PTB in different CMP configurations using realistic power numbers and heatsink/fan configurations. Results show how PTB not only balances temperature between the different cores, reducing temperature gradient and increasing signal reliability, but also allows a reduction of 28-30 % of both average and peak temperatures for the studied benchmarks when a peak power budget of 50 % is exceeded.
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| 12. |
- Chen, DeJiu, et al.
(författare)
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An architectural approach to the analysis, verification and validation of software intensive embedded systems
- 2013
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Ingår i: Computing. - : Springer Science and Business Media LLC. - 0010-485X .- 1436-5057. ; 95:8, s. 649-688
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Tidskriftsartikel (refereegranskat)abstract
- EAST-ADL is a domain specific Architecture Description Language (ADL) for safety-critical and software-intensive embedded systems. The language allows a formalized and traceable description of a wide range of engineering concerns throughout the entire lifecycle of system development. This makes it possible to fully utilize the leverage of state-of-the-art methods and tools for the development of correct-by-construction system functions and components in a seamless and cost efficient way. This paper focuses on the recent advancement of EAST-ADL in supporting an architecture-centric analysis, verification&validation of complex behaviors for the purposes of requirements engineering, application design, and safety engineering. The approach is architecture centric because all behavior descriptions are formalized and connected to a set of standardized design artifacts sitting at multiple levels of abstractions. We present the language design to support this, the theoretical underpinning and tool implementation. To show the capability of EAST-ADL, we also introduce an algorithm and its implementation for transforming the EAST-ADL behavior models to SPIN models for logic model checking. Exploiting mature state-of-the-art technologies from computer science, electronic engineering, and other related domains for a model-based incremental system development, the contribution enables the developers of embedded systems and software to maintain various engineering concerns coherently using EAST-ADL.
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| 13. |
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| 14. |
- Dastgeer, Usman, 1985-, et al.
(författare)
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The PEPPHER composition tool : performance-aware composition for GPU-based systems
- 2014
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Ingår i: Computing. - : Springer. - 0010-485X .- 1436-5057. ; 96:12, s. 1195-1211
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Tidskriftsartikel (refereegranskat)abstract
- The PEPPHER (EU FP7 project) component model defines the notion of component, interface and meta-data for homogeneous and heterogeneous parallel systems. In this paper, we describe and evaluate the PEPPHER composition tool, which explores the application’s components and their implementation variants, generates the necessary low-level code that interacts with the runtime system, and coordinates the native compilation and linking of the various code units to compose the overall application code to optimize performance. We discuss the concept of smart containers and its benefits for reducing dispatch overhead, exploiting implicit parallelism across component invocations and runtime optimization of data transfers. In an experimental evaluation with several applications, we demonstrate that the composition tool provides a high-level programming front-end while effectively utilizing the task-based PEPPHER runtime system (StarPU) underneath for different usage scenarios on GPU-based systems.
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| 15. |
- Ebrahimi, Masoumeh, et al.
(författare)
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A Light-weight fault-tolerant routing algorithm tolerating faulty links and routers
- 2013
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Ingår i: Computing. - : Springer Science and Business Media LLC. - 0010-485X .- 1436-5057. ; 97, s. 631-648
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Tidskriftsartikel (refereegranskat)abstract
- Faults at either the link or router level may result in the failure of the system. Fault-tolerant routing algorithms attempt to tolerate faults by rerouting packets around the faulty region. This rerouting would be at the cost of significant performance loss. The proposed algorithm in this paper is able to tolerate both faulty routers and links with negligible impact on the performance. In fact, the proposed algorithm avoids taking unnecessary longer paths and the shortest paths are always taken as long as a path exists. On the other hand, fault-tolerant routing algorithms might be based on deterministic routing in which all packets use a single path between each pair of source and destination routers. Using deterministic routing, packets reach the destination in the same order they have been delivered from the source so that no reordering buffer is needed at the destination. For improving the performance, fault-tolerant algorithms might be based on adaptive routing in which packets are delivered through multiple paths to destinations. In this case, packets should be reordered at the destinations demanding reordering buffers. The proposed algorithm can be configured in both working modes, such that it can be based on deterministic or adaptive routing.
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| 16. |
- Fakhouri, Hussam N., et al.
(författare)
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Four vector intelligent metaheuristic for data optimization
- 2024
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Ingår i: Computing. - : Springer. - 0010-485X .- 1436-5057. ; 106:7, s. 2321-2359
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Tidskriftsartikel (refereegranskat)abstract
- Swarm intelligence (SI) algorithms represent a class of Artificial Intelligence (AI) optimization metaheuristics used for solving complex optimization problems. However, a key challenge in solving complex problems is maintaining the balance between exploration and exploitation to find the optimal global solution and avoid local minima. This paper proposes an innovative Swarm Intelligence (SI) algorithm called the Four Vector Intelligent Metaheuristic (FVIM) to address the aforementioned problem. FVIM’s search strategy is guided by four top-performing leaders within a swarm, ensuring a balanced exploration-exploitation trade-off in the search space, avoiding local minima, and mitigating low convergence issues. The efficacy of FVIM is evaluated through extensive experiments conducted over two datasets, incorporating both qualitative and quantitative statistical measurements. One dataset contains twenty-three well-known single-objective optimization functions, such as fixed-dimensional and multi-modal functions, while the other dataset comprises the CEC2017 functions. Additionally, the Wilcoxon test was computed to validate the result’s significance. The results illustrate FVIM’s effectiveness in addressing diverse optimization challenges. Moreover, FVIM has been successfully applied to tackle engineering design problems, such as weld beam and truss engineering design. © The Author(s), under exclusive licence to Springer-Verlag GmbH Austria, part of Springer Nature 2024.
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| 17. |
- Fallah, Mohammad K., et al.
(författare)
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A symbiosis between population based incremental learning and LP-relaxation based parallel genetic algorithm for solving integer linear programming models
- 2024
-
Ingår i: Computing. - : Springer Science and Business Media LLC. - 0010-485X .- 1436-5057.
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Tidskriftsartikel (refereegranskat)abstract
- Solving Integer Linear Programming (ILP) models generally lies in the category of NP-hard problems and finding the optimal answer for large models is a computational challenge. Genetic algorithms are a family of metaheuristic algorithms capable of adjusting and redesigning parameters and operations according to the characteristics of ILP models. On the other hand, still the genetic algorithm performs a lot of operations to solve large models, and parallel processing is a suitable technique to tackle this problem. This paper introduces an LP-Relaxation based parallel genetic algorithm that uses a population-based incremental learning technique to presents an expandable solver for large ILP models derived from a behavioral synthesis of digital circuits. In the proposed algorithm, each chromosome provides a state subspace of possible solutions, and each generation is produced based on a probability vector as well as elitism. Our experiments verify the efficiency of the proposed algorithm on multicore platforms, as it outperformed four previous genetic algorithms for solving mixed integer programming problems. The proposed genetic algorithm solved 20 ILP models include up to 5183 int / binary decision variables in less than 20 min using four 16-core AMD Opteron 6386 SE processors. Also, the results indicate that for models with more than 4000 variables, the speedup and the efficiency of the proposed parallel genetic algorithm on 60 CPU cores is more than 18X and 30%, respectively.
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| 18. |
- Jäger, Gerold
(författare)
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Reduction of Smith Normal Form Transformation Matrices
- 2005
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Ingår i: Computing. - : Springer. - 0010-485X .- 1436-5057. ; 74:4, s. 377-388
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Tidskriftsartikel (refereegranskat)abstract
- Smith normal form computations are important in group theory, module theory and number theory. We consider the transformation matrices for the Smith normal form over the integers and give a presentation of arbitrary transformation matrices for this normal form. Our main contribution is an algorithm that replaces already computed transformation matrices by others with small entries. We combine methods from lattice basis reduction with a procedure to reduce the sum of the squared entries of both transformation matrices. This algorithm performs well even for matrices of large dimensions.
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| 19. |
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| 20. |
- Memeti, Suejb, et al.
(författare)
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Optimization of heterogeneous systems with AI planning heuristics and machine learning : a performance and energy aware approach
- 2021
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Ingår i: Computing. - : Springer. - 0010-485X .- 1436-5057. ; 103, s. 2943-2966
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Tidskriftsartikel (refereegranskat)abstract
- Heterogeneous computing systems provide high performance and energy efficiency. However, to optimally utilize such systems, solutions that distribute the work across host CPUs and accelerating devices are needed. In this paper, we present a performance and energy aware approach that combines AI planning heuristics for parameter space exploration with a machine learning model for performance and energy evaluation to determine a near-optimal system configuration. For data-parallel applications our approach determines a near-optimal host-device distribution of work, number of processing units required and the corresponding scheduling strategy. We evaluate our approach for various heterogeneous systems accelerated with GPU or the Intel Xeon Phi. The experimental results demonstrate that our approach finds a near-optimal system configuration by evaluating only about 7% of reasonable configurations. Furthermore, the performance per Joule estimation of system configurations using our machine learning model is more than 1000 x faster compared to the system evaluation by program execution.
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| 21. |
- Memeti, Suejb, et al.
(författare)
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Using meta-heuristics and machine learning for software optimization of parallel computing systems : a systematic literature review
- 2019
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Ingår i: Computing. - : Springer. - 0010-485X .- 1436-5057. ; 101:8, s. 893-936
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Tidskriftsartikel (refereegranskat)abstract
- While modern parallel computing systems offer high performance, utilizing these powerful computing resources to the highest possible extent demands advanced knowledge of various hardware architectures and parallel programming models. Furthermore, optimized software execution on parallel computing systems demands consideration of many parameters at compile-time and run-time. Determining the optimal set of parameters in a given execution context is a complex task, and therefore to address this issue researchers have proposed different approaches that use heuristic search or machine learning. In this paper, we undertake a systematic literature review to aggregate, analyze and classify the existing software optimization methods for parallel computing systems. We review approaches that use machine learning or meta-heuristics for software optimization at compile-time and run-time. Additionally, we discuss challenges and future research directions. The results of this study may help to better understand the state-of-the-art techniques that use machine learning and meta-heuristics to deal with the complexity of software optimization for parallel computing systems. Furthermore, it may aid in understanding the limitations of existing approaches and identification of areas for improvement.
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| 22. |
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| 23. |
- Payberah, Amir H., 1978-, et al.
(författare)
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Distributed optimization of P2P live streaming overlays
- 2012
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Ingår i: Computing. - : Springer Science and Business Media LLC. - 0010-485X .- 1436-5057. ; 94:8-10, s. 621-647
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Tidskriftsartikel (refereegranskat)abstract
- Peer-to-peer live media streaming over the Internet is becoming increasingly more popular, though it is still a challenging problem. Nodes should receive the stream with respect to intrinsic timing constraints, while the overlay should adapt to the changes in the network and the nodes should be incentivized to contribute their resources. In this work, we meet these contradictory requirements simultaneously, by introducing a distributed market model to build an efficient overlay for live media streaming. Using our market model, we construct two different overlay topologies, tree-based and mesh-based, which are the two dominant approaches to the media distribution. First, we build an approximately minimal height multiple-tree data dissemination overlay, called Sepidar. Next, we extend our model, in GLive, to make it more robust in dynamic networks by replacing the tree structure with a mesh. We show in simulation that the mesh-based overlay outperforms the multiple-tree overlay. We compare the performance of our two systems with the state-of-the-art NewCoolstrea-ming, and observe that they provide better playback continuity and lower playback latency than that of NewCoolstreaming under a variety of experimental scenarios. Although our distributed market model can be run against a random sample of nodes, we improve its convergence time by executing it against a sample of nodes taken from the Gradient overlay. The evaluations show that the streaming overlays converge faster when our market model works on top of the Gradient overlay.
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| 24. |
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| 25. |
- Taghinezhad-Niar, Ahmad, et al.
(författare)
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Energy-efficient workflow scheduling with budget-deadline constraints for cloud
- 2022
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Ingår i: Computing. - : Springer. - 0010-485X .- 1436-5057. ; 104:3, s. 601-625
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Tidskriftsartikel (refereegranskat)abstract
- Cloud computing has become a well-known platform for solving big data and complex problems such as workflow applications. Infrastructure as a Service (IaaS) from the cloud is a suitable platform to solve these problems as it can potentially provide a nearly unlimited amount of resources using virtualization technology with a pay-per-use cost model. Various Quality of Service (QoS) objectives, such as cost and time, have been considered individually for workflow scheduling. In this paper, we proposed two energy-efficient heuristic algorithms with budget-deadline constraints that are appropriate for resources with Dynamic Voltage and Frequency Scaling (DVFS) enabled, as well as those that do not support DVFS. They are Budget Deadline Constrained Energy-aware (BDCE) and Budget Deadline DVFS-enabled energy-aware (BDD) algorithms for the cloud. Furthermore, they acquire affordable cost, faster scheduling length, and higher energy-saving ratio. Various evaluation metrics like success rate, cost and time ratios, energy consumption, utilization rate, and energy-saving ratio are utilized to evaluate the performance of the proposed algorithms. The obtained results are compared with budget-deadline constraints methods, such as BDSD, DBCS, and BDHEFT, as well as two other energy-efficient deadline-constrained algorithms, namely, ERES and Safari's algorithm in various scenarios on scientific workflow applications.
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| 26. |
- Taheri, Javid, et al.
(författare)
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vmBBProfiler: A BlackBox Profiling Approach to Quantify Sensitivity of Virtual Machines to Shared Cloud Resources
- 2017
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Ingår i: Computing. - : Springer. - 0010-485X .- 1436-5057. ; 99:12, s. 1149-1177
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Tidskriftsartikel (refereegranskat)abstract
- Virtualized Data Centers are packed with numerous web and cloud servicesnowadays. In such large infrastructures, providing reliable service platforms dependsheavily on efficient sharing of physical machines (PMs) by virtual machines (VMs).To achieve efficient consolidation, performance degradation of co-located VMs mustbe correctly understood, modeled, and predicted. This work is a major step towardunderstanding such baffling phenomena by not only identifying, but also quantifyingsensitivity of general purpose VMs to their demanded resources. vmBBProfiler, ourproposed system in this work, is able to systematically profile behavior of any generalpurpose VM and calculate its sensitivity to system provided resources such as CPU,Memory, and Disk. vmBBProfiler is evaluated using 12 well-known benchmarks,varying from pure CPU/Mem/Disk VMs to mixtures of them, on three different PMsin our VMware-vSphere based private cloud. Extensive empirical results conductedover 1200h of profiling prove the efficiency of our proposed models and solutions; italso opens doors for further research in this area. vmBBProfiler: a black-box profiling approach to quantify sensitivity of virtual machines to shared cloud resources (PDF Download Available).
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| 27. |
- Vistbakka, I., et al.
(författare)
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Modelling resilient collaborative multi-agent systems
- 2021
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Ingår i: Computing. - : Springer Nature. - 0010-485X .- 1436-5057. ; 103:4, s. 535-557
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Tidskriftsartikel (refereegranskat)abstract
- Multi-agent systems constitute a wide class of decentralised systems. Their functions are usually carried out by collaborative activities of agents. To ensure resilience of multi-agent systems, we should endow them with a capability to dynamically reconfigure. Usually, as a result of reconfiguration, the existing relationships between agents are changed and new collaborations are established. This is a complex and error-prone process, which can be facilitated by the use of formal reasoning and automated verification. In this paper, we propose a generic resilience-explicit formalisation of the main concepts of multi-agent systems. Based on it, we introduce corresponding specification and refinement patterns in Event-B. Our patterns facilitate modelling behaviour of resilient multi-agent systems in a rigorous systematic way and verification of their properties. We demonstrate the application of the proposed approach by a case study—a smart warehouse system.
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