Earticle

Both performance and capacity of the main memory are the key to the computer systems in current architecture. DRAM, which is the most used main memory, can’t extend in capacity for its high energy consumption and repeatedly refresh. Fortunately, some new memory mediums, such as phase-change memory (PRAM), are used to replace traditional DRAM memory. These new memories have many advantages, like low energy consumption, without repeatedly refresh, high density storage, and so on. Therefore, these memories are promising. However, their low read/write performance and limited life are restricted the replacement process. In current time, hybrid memory, which consists of both PRAM and DRAM, is a good choice. In this way, the memory capacity can be extended. So, the most challenge for the hybrid memory is the performance. In this paper, we propose a dynamic hybrid LRU caching scheme (DH-LRU) for the last level cache in PRAM/DRAM hybrid main memory to improve the main memory performance. Compared with traditional cache policies, like LRU, FIFO, RANDOM, CFLRU, our DH-LRU improves performance by 4.6%. Moreover, energy consumption of write and read operation can be reduced up to 88.2%.

In order to study the effect of the internet of things (IOT) on the architecture of logistics service supply chain (LSSC), this paper summarizes the application of IOT in related fields on the basis of the theories of IOT, analyzes the effect of IOT on logistics/service flow, information flow and fund flow in LSSC and the effect on the structure of LSSC, builds the architecture of LSSC based on IOT, and finally forecasts the application prospect of IOT in LSSC.

Improving voltage stability, reducing real power loss (PL) and voltage deviation (VD) are the most important tasks in the operation of electrical power systems. Voltage instability and voltage collapse are the severe problems which may take place because of deficit reactive power at load buses due to increased loading or contingencies. In this paper, the problem of obtaining optimal location and size of SVC is formulated as true multi-objective optimization problem for simultaneous minimization of the two objectives namely real power losses and load bus voltage deviation. The two algorithms real coded genetic algorithm (RCGA) and non-dominated sorting genetic algorithm-II (NSGA-II) with a feature of adoptive crowding distance have been used for solving nonlinear constrained multi-objective optimization problem. Both the algorithms have been used for obtaining optimal location and sizing of SVC. Voltage security of the power system has also been analyzed separately for all placement of SVC to ensure secure operation of the system. The proposed approaches have been implemented on IEEE 30-bus test system. The simulation results of the two algorithms have been compared for solution quality, computational complexity and computational time. It has been found that NSGA-II presents better performance in solving multi-objective optimization problem and also in obtaining a diverse set of solutions which converge near the true Pareto-optimal front. The simulation results of NSGA-II have also been presented to exhibit the capabilities of the algorithm to generate well-distributed Pareto-optimal front.

The current investment and management mode of power grid construction project is inadequate to the whole optimization, the overall process of the project has obvious time-phased, therefore, the paper strongly advocates to carry out life-cycle management in power grid construction project, and divides the construction project into five stages as preliminary planning, design and planning, construction and operation, scrap and disposal, and evaluate and control the cost of operating stage, investment benefit of decision stage, design stage management and risk of construction stage, and sets up performance evaluation model of power grid project, in order to provide certain practical significance for the establishment of life-cycle management mode of power grid enterprises.

Wireless body area network (WBAN) is a communication standard optimized for low power devices and operation on, in or around the human body but not limited to humans used to serve a variety of applications including medical, consumer electronics, entertainment and other[1]. The challenge of WBAN is that the energy of the sensors is limited by the battery life that’s why the transmitting of data is not continuous for long time. This leads to poor efficiency of the WBAN because the continuous power decreasing is due to network operations. An algorithms such as MAC zigbee802.15.4 and adaptive reliable MAC are important to reduce the replacement of batteries many times and to save power consumption. In this paper we concentrated our study on some type of sensors, they are telosB, mica2, micaz, and imote2 depends on power consumption calculations using mat lab program and based on adaptive reliable MAC. We analyzed the sensors with several nodes and packet sizes, and calculate the lifetimes for all the sensors in WBAN. The results we obtained show a good performance of using Adaptive reliable MAC in Wireless Body Area Networks.

Cloud Computing is one of the major trends in today’s information technology and the most likely research area. Cloud Computing is a model of sharing resources, software, information. The user access the cloud via internet and all the resources are open to all. Thus, cloud security is now a challenging problem for the cloud service providers. Cryptography is a good solution of the cloud security and several research works are published to ensure secure cloud using cryptographic tools. This paper proposes an authentic communication between a customer and cloud service provider using encryption, decryption and message digests.

Clustering is one of the effective methods which are applied in the wireless sensor networks to preserve the precious battery power of sensor nodes. Various clustering approaches have been proposed in the literature and LEACH is one of clustering and routing schemes which can be used to manage the sensor network. In this paper, we present an improved version of LEACH protocol which uses Kmeans clustering algorithm for selecting better nodes for clusterhead role. Our proposed solution tries to create symmetric clusters and by reducing the average intra-cluster communications distance, improves the network lifetime. It also, considers the sink location when the sink node is positioned far away and selects nodes as clusterhead which will consume less energy for handling cluster members. Thus, because, sensed data are transmitted to the closer clusterheads, our proposed clustering solution can prolong the network lifetime.

In the virtualization based cloud computing environment, multiple computers are allowed to run as virtual machines (VM) in a single physical computer. Efficient scheduling of limited underlying resources has been a key issue. This paper presents a formal method of CPU resources scheduling (FRS). VMs are divided into three resources statuses according to resources requirements and their run information. FRS scheduling is formally scheduling CPU resources according to the resources statuses. The implementation of FRS is confined to the VMM layer, without VM dependency. The evaluation shows that idle CPU resources of VMs are be used by those VMs which need more CPU resources and the CPU resources overall utilization is improved.