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See detailEnergy-Aware Scheduling on Multicore Heterogeneous Grid Computing Systems
Nesmachnow, sergio; Dorronsoro, bernabe; Pecero, Johnatan UL et al

in Journal of Grid Computing (2013), 11

We address a multicriteria nonpreemptive energy-aware scheduling problem for computationalGrid systems. This work introduces a new formulation of the scheduling problem for multicore heterogeneous ... [more ▼]

We address a multicriteria nonpreemptive energy-aware scheduling problem for computationalGrid systems. This work introduces a new formulation of the scheduling problem for multicore heterogeneous computational Grid systems in which the minimization of the energy consumption, along with the makespan metric, is considered. We adopt a two-level model, in which a meta-broker agent (level 1) receives all user tasks and schedules them on the available resources, belonging to different local providers (level 2). The computing capacity and energy consumption of resources are taken from real multi-core processors from the main current vendors. Twenty novel list scheduling methods for the problem are proposed, and a comparative analysis of all of them over a large set of problem instances is presented. Additionally, a scalability study is performed in order to analyze the contribution of the best new bi-objective list scheduling heuristics when the problem dimension grows. We conclude after the experimental analysis that accurate trade-off schedules are computed by using the new proposed methods. [less ▲]

Detailed reference viewed: 118 (0 UL)
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See detailEnergy-aware VM allocation on An Opportunistic Cloud Infrastructure
Diaz, Cesar UL; Castro, Harold; Villamizar, Mario et al

in Proceedings of the 13th IEEE/ACM International Symposium on Cluster, Cloud, and Grid Computing (2013)

UnaCloud is an opportunistic based cloud infras- tructure (IaaS) that allows to access on-demand computing capabilities using commodity desktops. Although UnaCloud maximizes the use of idle resources to ... [more ▼]

UnaCloud is an opportunistic based cloud infras- tructure (IaaS) that allows to access on-demand computing capabilities using commodity desktops. Although UnaCloud maximizes the use of idle resources to deploy virtual machines, it does not use energy-efficient resource allocation algorithms. In this paper, we design and develop different energy-aware algorithms to operate in an energy-efficient way and at the same time to guarantee the performance of the UnaCloud users. Performance tests with different algorithms and scenarios using real trace workloads from UnaCloud, show how different policies can change the energy consumption patterns and reduce the energy consumption in the opportunistic cloud infrastructure. The results show that some algorithms can reduce the energy-consumption power up to 30% over the percentage earned by the opportunistic environment [less ▲]

Detailed reference viewed: 153 (0 UL)
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See detailEnergy-Efficient and Secure Resource Allocation for Multiple-Antenna NOMA with Wireless Power Transfer
Chang, Zheng; Lei, Lei UL; Zhang, Huaqing et al

in IEEE Transactions on Green Communications and Networking (2018)

Detailed reference viewed: 135 (20 UL)
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See detailEnergy-efficient Communications in Cloud, Mobile Cloud and Fog Computing
Fiandrino, Claudio UL

Doctoral thesis (2016)

This thesis studies the problem of energy efficiency of communications in distributed computing paradigms, including cloud computing, mobile cloud computing and fog/edge computing. Distributed computing ... [more ▼]

This thesis studies the problem of energy efficiency of communications in distributed computing paradigms, including cloud computing, mobile cloud computing and fog/edge computing. Distributed computing paradigms have significantly changed the way of doing business. With cloud computing, companies and end users can access the vast majority services online through a virtualized environment in a pay-as-you-go basis. %Three are the main services typically consumed by cloud users are Infrastructure as a Service (IaaS), Platform as a Service (PaaS) and Software as a Service (SaaS). Mobile cloud and fog/edge computing are the natural extension of the cloud computing paradigm for mobile and Internet of Things (IoT) devices. Based on offloading, the process of outsourcing computing tasks from mobile devices to the cloud, mobile cloud and fog/edge computing paradigms have become popular techniques to augment the capabilities of the mobile devices and to reduce their battery drain. Being equipped with a number of sensors, the proliferation of mobile and IoT devices has given rise to a new cloud-based paradigm for collecting data, which is called mobile crowdsensing as for proper operation it requires a large number of participants. A plethora of communication technologies is applicable to distributing computing paradigms. For example, cloud data centers typically implement wired technologies while mobile cloud and fog/edge environments exploit wireless technologies such as 3G/4G, WiFi and Bluetooth. Communication technologies directly impact the performance and the energy drain of the system. This Ph.D. thesis analyzes from a global perspective the efficiency in using energy of communications systems in distributed computing paradigms. In particular, the following contributions are proposed: - A new framework of performance metrics for communication systems of cloud computing data centers. The proposed framework allows a fine-grain analysis and comparison of communication systems, processes, and protocols, defining their influence on the performance of cloud applications. - A novel model for the problem of computation offloading, which describes the workflow of mobile applications through a new Directed Acyclic Graph (DAG) technique. This methodology is suitable for IoT devices working in fog computing environments and was used to design an Android application, called TreeGlass, which performs recognition of trees using Google Glass. TreeGlass is evaluated experimentally in different offloading scenarios by measuring battery drain and time of execution as key performance indicators. - In mobile crowdsensing systems, novel performance metrics and a new framework for data acquisition, which exploits a new policy for user recruitment. Performance of the framework are validated through CrowdSenSim, which is a new simulator designed for mobile crowdsensing activities in large scale urban scenarios. [less ▲]

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See detailEnergy-Efficient Computation Offloading for Wearable Devices and Smartphones in Mobile Cloud Computing
Ragona, Claudio; Fiandrino, Claudio UL; Kliazovich, Dzmitry UL et al

in IEEE Global Communications Conference (GLOBECOM), San Diego, CA, USA, 2015 (2015, December)

Wearable devices are becoming increasingly popu- lar and are expected to become essential in our everyday life. De- spite continuous improvement of hardware, the lifetime of mobile devices and their ... [more ▼]

Wearable devices are becoming increasingly popu- lar and are expected to become essential in our everyday life. De- spite continuous improvement of hardware, the lifetime of mobile devices and their capabilities still remain a concern. Small size of batteries of smart watches, glasses, helmets and gloves limits the amount of computing, storage and communication resources. Mobile cloud computing can augment the capabilities of wearable devices by helping to execute some of the computing tasks in the cloud. Such computational offloading helps to preserve battery power at the cost of more intensive communications with the cloud. In this paper, we present a model and comprehensive analysis for computational offloading between wearable devices and clouds in realistic setups. [less ▲]

Detailed reference viewed: 425 (21 UL)
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See detailEnergy-Efficient Computing using Agent-Based Multi-Objective Dynamic Optimization
Tantar, Alexandru-Adrian UL; Danoy, Grégoire UL; Bouvry, Pascal UL et al

in J. H. Kim and M. J. Lee (Ed.) Green IT: Technologies and Applications (2011)

Detailed reference viewed: 114 (9 UL)
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See detailEnergy-efficient coordinated multi-cell multi-group multicast beamforming with antenna selection
Tervo, O.; Tran, L. N.; Pennanen, H. et al

in 2017 IEEE International Conference on Communications Workshops (ICC) (2017)

Detailed reference viewed: 99 (0 UL)
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See detailEnergy-Efficient Data Acquisition in Mobile Crowdsensing Systems
Capponi, Andrea UL

in 19th IEEE International Symposium on a World of Wireless, Mobile and Multimedia Networks (WoWMoM), Chania, Greece, 2018 (2018, June)

Mobile Crowdsensing (MCS) is one of the most promising paradigms for monitoring phenomena in urban environments. The success of a MCS campaign relies on large participation of citizens, who may be ... [more ▼]

Mobile Crowdsensing (MCS) is one of the most promising paradigms for monitoring phenomena in urban environments. The success of a MCS campaign relies on large participation of citizens, who may be reluctant in joining a campaign due to sensing and reporting costs they sustain. Hence, it is fundamental to propose efficient data collection frameworks (DCFs). In the first stages of our work, we proposed an energyefficient DCF that aims to minimize energy consumption while maximizing the utility of contributed data. Then, we developed an Android application and proposed a methodology to compare several DCFs, performing energy- and network-related measures with Power Monitor and Wireshark. Currently, we are investigating collaborative data delivery as a more efficient solution than the individual one. The key idea is to form groups of users and elect a responsible for aggregated data delivery. To this end, it is crucial to analyze device to device (D2D) communications and propose efficient policies for group formation and owner election. To evaluate the performance in realistic urban environments we exploit CrowdSenSim, which runs large-scale simulations in citywide scenarios. [less ▲]

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See detailEnergy-Efficient Data Replication in Cloud Computing Datacenters
Boru, Dejene; Kliazovich, Dzmitry UL; Granelli, Fabrizio et al

in IEEE Globecom 2013 International Workshop on Cloud Computing Systems, Networks, and Applications (CCSNA), Atlanta, GA, USA, 2013 (2013)

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See detailEnergy-efficient Data Replication in Cloud Computing Datacenters
Boru, Dejene; Kliazovich, Dzmitry UL; Granelli, Fabrizio et al

in Cluster Computing (2015), 18(1), 385-402

Cloud computing is an emerging paradigm that provides computing, communication and storage resources as a service over a network. Communication resources often become a bottleneck in service provisioning ... [more ▼]

Cloud computing is an emerging paradigm that provides computing, communication and storage resources as a service over a network. Communication resources often become a bottleneck in service provisioning for many cloud applications. Therefore, data replication which brings data (e.g., databases) closer to data consumers (e.g., cloud applications) is seen as a promising solution. It allows minimizing network delays and bandwidth usage. In this paper we study data replication in cloud computing data centers. Unlike other approaches available in the literature, we consider both energy efficiency and bandwidth consumption of the system. This is in addition to the improved quality of service QoS obtained as a result of the reduced communication delays. The evaluation results, obtained from both mathematical model and extensive simulations, help to unveil performance and energy efficiency tradeoffs as well as guide the design of future data replication solutions. [less ▲]

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See detailEnergy-efficient deployment in wireless edge caching
Vu, Thang Xuan UL; Chatzinotas, Symeon UL; Ottersten, Björn UL

in Wireless Edge Caching: Modeling, Analysis, and Optimization (2020)

In this chapter, we investigate the performance of edge-caching wireless networks by taking into account the caching capability when designing the signal transmission. We consider hierarchical caching ... [more ▼]

In this chapter, we investigate the performance of edge-caching wireless networks by taking into account the caching capability when designing the signal transmission. We consider hierarchical caching systems in which the contents can be prefetched at both user terminals or the base station and investigate the energy performance under two notable uncoded and coded caching strategies. The backhaul and access throughputs are derived for both caching policies for arbitrary values of base station and user cache sizes from which closed-form expressions for the corresponding system energy efficiency (EE) are obtained. Furthermore, we propose two optimization problems to maximize the system EE and minimize the content delivery time subject to some given quality of service requirements. [less ▲]

Detailed reference viewed: 55 (4 UL)
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See detailEnergy-Efficient Design for Edge-caching Wireless Networks: When is Coded-caching beneficial?
Vu, Thang Xuan UL; Chatzinotas, Symeon UL; Ottersten, Björn UL

in Proceedings of IEEE 18th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC) (2017, July)

Detailed reference viewed: 161 (19 UL)
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See detailEnergy-efficient design for latency-tolerant content delivery networks
Vu, Thang Xuan UL; Lei, Lei UL; Vuppala, Satyanarayana et al

in 2018 IEEE Wireless Communications and Networking Conference (WCNC) (2018, May)

Detailed reference viewed: 119 (19 UL)
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See detailEnergy-Efficient Distributed Spectrum Sensing for Cognitive Sensor Networks
Maleki, Sina UL; Pandharipande, Ashish; Leus, Geert

in IEEE Sensors Journal (2011), 11(3), 565-573

Reliability and energy consumption in detection are key objectives for distributed spectrum sensing in cognitive sensor networks. In conventional distributed sensing approaches, although the detection ... [more ▼]

Reliability and energy consumption in detection are key objectives for distributed spectrum sensing in cognitive sensor networks. In conventional distributed sensing approaches, although the detection performance improves with the number of radios, so does the network energy consumption. We consider a combined sleeping and censoring scheme as an energy efficient spectrum sensing technique for cognitive sensor networks. Our objective is to minimize the energy consumed in distributed sensing subject to constraints on the detection performance, by optimally choosing the sleeping and censoring design parameters. The constraint on the detection performance is given by a minimum target probability of detection and a maximum permissible probability of false alarm. Depending on the availability of prior knowledge about the probability of primary user presence, two cases are considered. The case where a priori knowledge is not available defines the blind setup; otherwise the setup is called knowledge-aided. By considering a sensor network based on IEEE 802.15.4/ZigBee radios, we show that significant energy savings can be achieved by the proposed scheme. [less ▲]

Detailed reference viewed: 115 (4 UL)
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See detailEnergy-efficient distributed spectrum sensing with convex optimization
Maleki, Sina UL; Pandharipande, Ashish; Leus, Geert

in 3rd IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP), 2009 (2009, December)

We consider the problem of distributed spectrum sensing in cognitive radio networks with a central fusion center, from an energy efficiency viewpoint. In our scheme, each cognitive radio adopts a ... [more ▼]

We consider the problem of distributed spectrum sensing in cognitive radio networks with a central fusion center, from an energy efficiency viewpoint. In our scheme, each cognitive radio adopts a combination of sleeping and censoring to obtain a sensing result based on energy detection, while the fusion center combines all the sensing results using an OR decision rule. Our goal is to minimize the network energy consumption, given constraints on the global probabilities of detection and false-alarm. We show that the underlying optimization problem can be solved as a convex optimization problem. We then show the energy efficiency of our scheme via simulations using a ZigBee transceiver model. [less ▲]

Detailed reference viewed: 97 (4 UL)
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See detailEnergy-Efficient Driver Assistance System for Electric Vehicles Using Model-Predictive Control
Schwickart, Tim Klemens UL

Doctoral thesis (2015)

This thesis investigates a method to save energy and thus also extend the range of a series-production battery electric vehicle by influencing the driving style automatically with the help of a of a ... [more ▼]

This thesis investigates a method to save energy and thus also extend the range of a series-production battery electric vehicle by influencing the driving style automatically with the help of a of a cruise controller. An exploration of existing methods shows that the contextual consideration of the current and upcoming driving situation is necessary to realise safe and energy-efficient driving. This limits the appropriate approaches to online methods using updated predictions of the vehicle behaviour. It turns out that the most suitable method for the intended purpose is model-predictive control (MPC). The MPC generates controls for the accelerator pedal of the vehicle based on optimised predictions of the vehicle motion and energy consumption subject to the current and future road slope, curvature, speed limits and distance to an eventually preceding vehicle. The non-linear nature of the vehicle dynamics generally necessitates the use of a non-linear prediction model and solving a non-linear optimisation which goes along with difficulties in the online real-time implementation. However in this work - by exploiting and extending the tool sets of classical MPC - a controller based on a quadratic optimal control problem with linear constraints can be formulated that approximates the nonlinearities of the plant dynamics with equivalent accuracy as a non-linear formulation. A linear prediction model of the vehicle motion is derived by a change of the model domain from time to position and a change of variables to predict the kinetic energy of the moving vehicle instead of the driving speed. Further, a convex piece-wise linear energy consumption model is included in the inequality constraints of the problem according to the methodology of separable programming to capture the consumption characteristics of the vehicle in different operating points. In this form, real-time capability and the energy-saving potential of the presented control approach can be demonstrated by simulations of the closed loop and by implementing the controller for driving experiments. A Smart ED series-production battery electric vehicle is chosen for the practical tests and all models and parameters are identified and adapted to the characteristics of the car. In this application case, a significant energy-saving potential could be demonstrated compared to human drivers. To further reduce the computational burden and speed up the computation, the so-called move blocking method for input parameterisation of the MPC control trajectory is investigated and extended within this work to a flexible move blocking approach which enables a fast computation and at the same time high tracking performance. [less ▲]

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See detailEnergy-Efficient Elliptic Curve Cryptography for MSP430-Based Wireless Sensor Nodes
Liu, Zhe UL; Groszschädl, Johann UL; Li, Lin et al

in Liu, Joseph K.; Steinfeld, Ron (Eds.) Information Security and Privacy - 21st Australasian Conference, ACISP 2016, Melbourne, VIC, Australia, July 4-6, 2016, Proceedings, Part I (2016, July)

The Internet is rapidly evolving from a network of personal computers and servers to a network of smart objects ("things") able to communicate with each other and with central resources. This evolution ... [more ▼]

The Internet is rapidly evolving from a network of personal computers and servers to a network of smart objects ("things") able to communicate with each other and with central resources. This evolution has created a demand for lightweight implementations of cryptographic algorithms suitable for resource-constrained devices such as RFID tags and wireless sensor nodes. In this paper we describe a highly optimized software implementation of Elliptic Curve Cryptography (ECC) for the MSP430 series of ultra-low-power 16-bit microcontrollers. Our software is scalable in the sense that it supports prime fields and elliptic curves of different order without recompilation, which allows for flexible trade-offs between execution time (i.e. energy consumption) and security. The low-level modular arithmetic is optimized for pseudo-Mersenne primes of the form p = 2^n - c where n is a multiple of 16 minus 1 and c fits in a 16-bit register. All prime-field arithmetic functions are parameterized with respect to the length of operands (i.e. the number of 16-bit words they consist of) and written in Assembly language, whereby we avoided conditional jumps and branches that could leak information about the secret key. Our ECC implementation can perform scalar multiplication on two types of elliptic curves, namely Montgomery curves and twisted Edwards curves. A full scalar multiplication using a Montgomery curve over a 159-bit field requires about 3.86*10^6 clock cycles when executed on an MSP430F1611 microcontroller. [less ▲]

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See detailEnergy-efficient joint unicast and multicast beamforming with multi-antenna user terminals
Tervo, O.; Tran, L. N.; Chatzinotas, Symeon UL et al

in 2017 IEEE 18th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC) (2017)

Detailed reference viewed: 95 (1 UL)
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See detailEnergy-Efficient MMSE Beamforming and Power Optimization in Multibeam Satellite Systems
Chatzinotas, Symeon UL; Zheng, Gan UL; Ottersten, Björn UL

in Energy-Efficient MMSE Beamforming and Power Optimization in Multibeam Satellite Systems (2011)

Detailed reference viewed: 115 (6 UL)
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See detailEnergy-Efficient Multicell Multigroup Multicasting With Joint Beamforming and Antenna Selection
Tervo, Oskari; Tran, Le-Nam; Pennanen, Harri et al

in IEEE Transactions on Signal Processing (2018)

Detailed reference viewed: 85 (6 UL)