Energy consumption is a crucially important issue in battery-driven wireless sensor networks (WSNs). In most sensor networks, the sensors near the data collector (i.e. the sink) become drained more quickly than those elsewhere in the network since they are required to relay all of the data collected in the network to the sink. Therefore more balanced data paths to the sink should be established in order to extend the lifetime of the sensor network. Accordingly, a novel relay deployment scheme for WSNs based on the Voronoi diagram is proposed. The proposed scheme is applicable to both two-dimensional and three-dimensional network topologies and establishes effective routing paths that balance the traffic load within the sensor network and alleviate the burden on the sensors around the sink. Simulation results indicate that the number of relays deployed in the proposed scheme is similar to that deployed in the predetermined location scheme and is significantly less than that deployed in the minimum set cover scheme. Furthermore, the lifetime of the sensor network containing relay nodes deployed using the current scheme is longer than that achieved using either the predetermined location scheme or the minimum set cover scheme.
To achieve coordinated functions, fluidic soft robots typically rely on multiple input lines for the independent inflation and deflation of each actuator. Fluidic actuators are controlled by rigid electronic pneumatic valves, restricting the mobility and compliance of the soft robot. Recent developments in soft valve designs have shown the potential to achieve a more integrated robotic system, but are limited by high energy consumption and slow response time. In this work, we present an electropermanent magnet (EPM) valve for electronic control of pneumatic soft actuators that is activated through microsecond electronic pulses. The valve incorporates a thin channel made from thermoplastic films. The proposed valve (3 × 3 × 0.8 cm, 2.9 g) can block pressure up to 146 kPa and negative pressures up to –100 kPa with a response time of less than 1 s. Using the EPM valves, we demonstrate the ability to switch between multiple operation sequences in real time through the control of a six-DoF robot capable of grasping and hopping with a single pressure input. Our proposed onboard control strategy simplifies the operation of multi-pressure systems, enabling the development of dynamically programmable soft fluid-driven robots that are versatile in responding to different tasks. Ranzani and colleagues use electropermanent magnets to build a valve that simplifies the controls of pneumatic soft robots. Their design enables the selective activation of the robot's fluidic channels to perform grasping and locomotion tasks.
This paper has two parts: Firstly, we investigate today's ATM network, especially the most load NFS applications. Secondly, we propose a fast simulation based on fractional ARIMA processes and an importance sampling scheme. In our collected data, we have found the traffic characteristics of today's ATM network present both long range dependence (LRD) and short range dependence (SRD) structures. Because of the strong SRD and LRD of the empirical traces, models which can present both LRD and SRD are necessary to simulate the traffic of today's networks. However, traditional Monte Carlo simulations with long range dependent structure make the cost of the computation very large and for CLP (cell loss probability)<10/sup -9/ traditional Monte Carlo simulations are almost impossible to achieve it. The proposed fast ARIMA simulation based on importance sampling efficient to simulate the queuing performance with self-similar inputs which exhibit both SRD and LRD properties.
DiffServ provides class-based differentiated quality of service (QoS). For perception of users, flow-based service differentiation is much more important than class-based. Class-based QoS per-hop behaviour (PHB) is ensured in a DiffServ router. However, a flow in a higher class may get worse QoS than a flow in a lower class due to unbalanced traffic conditions. Therefore, a novel scheme with a Bloom-filter-based estimator for number of active flows, a dynamic weighted fair queueing (WFQ) scheduler, and a queue management mechanism to provide flow-based proportional QoS differentiation is proposed. This scheme dynamically adapts the WFQ weight of each class according to estimations of numbers of active flows in each class to provide proportional bandwidth differentiation for flows in different classes. Furthermore, a queue management mechanism with estimation of numbers of active flows and queue length feedback control is employed to control the queue length of each class around a target value to achieve delay differentiation. Through detailed simulations, the proposed scheme is shown to be able to provide flow-based proportional bandwidth and delay differentiations for flows in different classes at the same time.
When a wireless mesh network accommodates interactive applications with quality of service requirements, schedule-based protocols are more suitable than contention-based protocols. In this paper, the problem of determining an appropriate schedule assignment for multiple group transmissions within a spatial time division multiple access link scheduling network is referred to as an integrated multiple-group communication and link scheduling problem. A polynomial-time scheduling algorithm, designated as a source-parallel-aware assignment (SPAA), is proposed to increase the spatial utilisation within each time slot in order to enhance the network throughput. Furthermore, an advanced version of SPAA, designated as joint source-parallel-aware assignment with network coding (JSANC), is proposed to reduce the effects of bottleneck paths on the schedule frame length by flexibly applying conventional or opportunistic network coding approaches. Simulation results show that the proposed algorithms achieve a better network throughput than existing flow-based or particular order-based scheduling schemes.
'/%3e%3cuse xlink:href='%23a' transform='rotate(60)'/%3e%3ccircle r='17' fill='%23000095'/%3e%3ccircle r='15' fill='%23fff'/%3e%3c/svg%3e)
'/%3e%3cuse xlink:href='%23a' transform='rotate(23.036 .093 25.536)'/%3e%3cuse xlink:href='%23a' transform='rotate(45.87 1.273 16.18)'/%3e%3cuse xlink:href='%23a' transform='rotate(69.945 .996 12.078)'/%3e%3cuse xlink:href='%23a' transform='rotate(20.66 -19.689 31.932)'/%3e%3c/svg%3e)