With the popularity of green computing and the huge usage of networks,there is an acute need for expansion of the 5G network.5G is used where energy efficiency is the highest priority,and it can play a pinnacle role i...With the popularity of green computing and the huge usage of networks,there is an acute need for expansion of the 5G network.5G is used where energy efficiency is the highest priority,and it can play a pinnacle role in helping every industry to hit sustainability.While in the 5G network,conventional performance guides,such as network capacity and coverage are still major issues and need improvements.Device to Device communication(D2D)communication technology plays an important role to improve the capacity and coverage of 5G technology using different techniques.The issue of energy utilization in the IoT based system is a significant exploration center.Energy optimizationin D2D communication is an important point.We need to resolve this issue for increasing system performance.Green IoT speaks to the issue of lessening energy utilization of IoT gadgets which accomplishes a supportable climate for IoT systems.In this paper,we improve the capacity and coverage of 5G technology using Multiple Inputs Multiple Outputs(MU-MIMO).MUMIMO increases the capacity of 5G in D2D communication.We also present all the problems faced by 5G technology and proposed architecture to enhance system performance.展开更多
In this paper,we propose Triangular Code(TC),a new class of fountain code with near-zero redundancy and linear encoding and decoding computational complexities of OeLklog kT,where k is the packet batch size and L is t...In this paper,we propose Triangular Code(TC),a new class of fountain code with near-zero redundancy and linear encoding and decoding computational complexities of OeLklog kT,where k is the packet batch size and L is the packet data length.Different from previous works where the optimal performance of codes has been shown under asymptotic assumption,TC enjoys near-zero redundancy even under non-asymptotic settings for smallmoderate number of packets.These features make TC suitable for practical implementation in batteryconstrained devices in IoT,D2D and M2M network paradigms to achieve scalable reliability,and minimize latency due to its low decoding delay.TC is a non-linear code,which is encoded using the simple shift and XOR addition operations,and decoded using the simple back-substitution algorithm.Although it is nonlinear code at the packet level,it remains linear code when atomized at the bit level.We use this property to show that the backsubstitution decoder of TC is equivalent to the Belief Propagation(BP)decoder of LT code.Therefore,TC can benefit from rich prolific literature published on LT code,to design efficient code for various applications.Despite the equivalency between the decoders of TC and LT code,we show that compared to state-of-the-art optimized LT code,TC reduces the redundancy of LT code by 68%-99% for k reaching 1024.展开更多
The demand for cloud computing has increased manifold in the recent past.More specifically,on-demand computing has seen a rapid rise as organizations rely mostly on cloud service providers for their day-to-day computi...The demand for cloud computing has increased manifold in the recent past.More specifically,on-demand computing has seen a rapid rise as organizations rely mostly on cloud service providers for their day-to-day computing needs.The cloud service provider fulfills different user requirements using virtualization-where a single physical machine can host multiple VirtualMachines.Each virtualmachine potentially represents a different user environment such as operating system,programming environment,and applications.However,these cloud services use a large amount of electrical energy and produce greenhouse gases.To reduce the electricity cost and greenhouse gases,energy efficient algorithms must be designed.One specific area where energy efficient algorithms are required is virtual machine consolidation.With virtualmachine consolidation,the objective is to utilize the minimumpossible number of hosts to accommodate the required virtual machines,keeping in mind the service level agreement requirements.This research work formulates the virtual machine migration as an online problem and develops optimal offline and online algorithms for the single host virtual machine migration problem under a service level agreement constraint for an over-utilized host.The online algorithm is analyzed using a competitive analysis approach.In addition,an experimental analysis of the proposed algorithm on real-world data is conducted to showcase the improved performance of the proposed algorithm against the benchmark algorithms.Our proposed online algorithm consumed 25%less energy and performed 43%fewer migrations than the benchmark algorithms.展开更多
Sensors are often based on minimalistic microcontrollers for their reduced power consumption and size. Because of the specific hardware of sensors, their software development, including debugging, is also particular. ...Sensors are often based on minimalistic microcontrollers for their reduced power consumption and size. Because of the specific hardware of sensors, their software development, including debugging, is also particular. Simulators and external computers are conventional approaches to sensor debugging, but they both face limitations such as the supported hardware and debugging conditions. In this paper, we propose a fully autonomous on-chip debugging solution for sensors (and other devices) based on AVR microcontrollers, with a particular focus on human-machine interaction. The proposal is then validated in practice through various experiments, notably involving real-world sensors. Formal measurement of the induced overhead is also conducted, which eventually demonstrates the applicability of the proposal.展开更多
The Internet of Things (IoT) is emerging as an attractive paradigm involving physical perceptions, cyber interactions, social correlations and even cognitive thinking through a cyber-physical-social-thinking hyperspac...The Internet of Things (IoT) is emerging as an attractive paradigm involving physical perceptions, cyber interactions, social correlations and even cognitive thinking through a cyber-physical-social-thinking hyperspace. In this context, energy management with the purposes of energy saving and high efficiency is a challenging issue. In this work, a taxonomy model is established in reference to the IoT layers (i.e., sensor-actuator layer, network layer, and application layer), and IoT energy management is addressed from the perspectives of supply and demand to achieve green perception, communication, and computing. A smart home scenario is presented as a case study involving the main enabling technologies with supply-side, demand-side, and supply-demand balance considerations, and open issues in the field of IoT energy management are also discussed.展开更多
基金The authors extend their heartfelt thanks to the Department of Computer Science,College of Computer Science and Engineering,Taibah University Madinah,Saudi Arabia.
文摘With the popularity of green computing and the huge usage of networks,there is an acute need for expansion of the 5G network.5G is used where energy efficiency is the highest priority,and it can play a pinnacle role in helping every industry to hit sustainability.While in the 5G network,conventional performance guides,such as network capacity and coverage are still major issues and need improvements.Device to Device communication(D2D)communication technology plays an important role to improve the capacity and coverage of 5G technology using different techniques.The issue of energy utilization in the IoT based system is a significant exploration center.Energy optimizationin D2D communication is an important point.We need to resolve this issue for increasing system performance.Green IoT speaks to the issue of lessening energy utilization of IoT gadgets which accomplishes a supportable climate for IoT systems.In this paper,we improve the capacity and coverage of 5G technology using Multiple Inputs Multiple Outputs(MU-MIMO).MUMIMO increases the capacity of 5G in D2D communication.We also present all the problems faced by 5G technology and proposed architecture to enhance system performance.
文摘In this paper,we propose Triangular Code(TC),a new class of fountain code with near-zero redundancy and linear encoding and decoding computational complexities of OeLklog kT,where k is the packet batch size and L is the packet data length.Different from previous works where the optimal performance of codes has been shown under asymptotic assumption,TC enjoys near-zero redundancy even under non-asymptotic settings for smallmoderate number of packets.These features make TC suitable for practical implementation in batteryconstrained devices in IoT,D2D and M2M network paradigms to achieve scalable reliability,and minimize latency due to its low decoding delay.TC is a non-linear code,which is encoded using the simple shift and XOR addition operations,and decoded using the simple back-substitution algorithm.Although it is nonlinear code at the packet level,it remains linear code when atomized at the bit level.We use this property to show that the backsubstitution decoder of TC is equivalent to the Belief Propagation(BP)decoder of LT code.Therefore,TC can benefit from rich prolific literature published on LT code,to design efficient code for various applications.Despite the equivalency between the decoders of TC and LT code,we show that compared to state-of-the-art optimized LT code,TC reduces the redundancy of LT code by 68%-99% for k reaching 1024.
文摘The demand for cloud computing has increased manifold in the recent past.More specifically,on-demand computing has seen a rapid rise as organizations rely mostly on cloud service providers for their day-to-day computing needs.The cloud service provider fulfills different user requirements using virtualization-where a single physical machine can host multiple VirtualMachines.Each virtualmachine potentially represents a different user environment such as operating system,programming environment,and applications.However,these cloud services use a large amount of electrical energy and produce greenhouse gases.To reduce the electricity cost and greenhouse gases,energy efficient algorithms must be designed.One specific area where energy efficient algorithms are required is virtual machine consolidation.With virtualmachine consolidation,the objective is to utilize the minimumpossible number of hosts to accommodate the required virtual machines,keeping in mind the service level agreement requirements.This research work formulates the virtual machine migration as an online problem and develops optimal offline and online algorithms for the single host virtual machine migration problem under a service level agreement constraint for an over-utilized host.The online algorithm is analyzed using a competitive analysis approach.In addition,an experimental analysis of the proposed algorithm on real-world data is conducted to showcase the improved performance of the proposed algorithm against the benchmark algorithms.Our proposed online algorithm consumed 25%less energy and performed 43%fewer migrations than the benchmark algorithms.
文摘Sensors are often based on minimalistic microcontrollers for their reduced power consumption and size. Because of the specific hardware of sensors, their software development, including debugging, is also particular. Simulators and external computers are conventional approaches to sensor debugging, but they both face limitations such as the supported hardware and debugging conditions. In this paper, we propose a fully autonomous on-chip debugging solution for sensors (and other devices) based on AVR microcontrollers, with a particular focus on human-machine interaction. The proposal is then validated in practice through various experiments, notably involving real-world sensors. Formal measurement of the induced overhead is also conducted, which eventually demonstrates the applicability of the proposal.
文摘The Internet of Things (IoT) is emerging as an attractive paradigm involving physical perceptions, cyber interactions, social correlations and even cognitive thinking through a cyber-physical-social-thinking hyperspace. In this context, energy management with the purposes of energy saving and high efficiency is a challenging issue. In this work, a taxonomy model is established in reference to the IoT layers (i.e., sensor-actuator layer, network layer, and application layer), and IoT energy management is addressed from the perspectives of supply and demand to achieve green perception, communication, and computing. A smart home scenario is presented as a case study involving the main enabling technologies with supply-side, demand-side, and supply-demand balance considerations, and open issues in the field of IoT energy management are also discussed.
