792 resultados para Energy Efficient Mobile Network
Resumo:
Multicast in wireless sensor networks (WSNs) is an efficient way to spread the same data to multiple sensor nodes. It becomes more effective due to the broadcast nature of wireless link, where a message transmitted from one source is inherently received by all one-hop receivers, and therefore, there is no need to transmit the message one by one. Reliable multicast in WSNs is desirable for critical tasks like code updation and query based data collection. The erroneous nature of wireless medium coupled with limited resource of sensor nodes, makes the design of reliable multicast protocol a challenging task. In this work, we propose a time division multiple access (TDMA) based energy aware media access and control (TEA-MAC) protocol for reliable multicast in WSNs. The TDMA eliminates collisions, overhearing and idle listening, which are the main sources of reliability degradation and energy consumption. Furthermore, the proposed protocol is parametric in the sense that it can be used to trade-off reliability with energy and delay as per the requirement of the underlying applications. The performance of TEA-MAC has been evaluated by simulating it using Castalia network simulator. Simulation results show that TEA-MAC is able to considerably improve the performance of multicast communication in WSNs.
Resumo:
The nodes with dynamicity, and management without administrator are key features of mobile ad hoc networks (1VIANETs). Increasing resource requirements of nodes running different applications, scarcity of resources, and node mobility in MANETs are the important issues to be considered in allocation of resources. Moreover, management of limited resources for optimal allocation is a crucial task. In our proposed work we discuss a design of resource allocation protocol and its performance evaluation. The proposed protocol uses both static and mobile agents. The protocol does the distribution and parallelization of message propagation (mobile agent with information) in an efficient way to achieve scalability and speed up message delivery to the nodes in the sectors of the zones of a MANET. The protocol functionality has been simulated using Java Agent Development Environment (JADE) Framework for agent generation, migration and communication. A mobile agent migrates from central resource rich node with message and navigate autonomously in the zone of network until the boundary node. With the performance evaluation, it has been concluded that the proposed protocol consumes much less time to allocate the required resources to the nodes under requirement, utilize less network resources and increase the network scalability. (C) 2015 Elsevier B.V. All rights reserved.
Resumo:
A neural network is a highly interconnected set of simple processors. The many connections allow information to travel rapidly through the network, and due to their simplicity, many processors in one network are feasible. Together these properties imply that we can build efficient massively parallel machines using neural networks. The primary problem is how do we specify the interconnections in a neural network. The various approaches developed so far such as outer product, learning algorithm, or energy function suffer from the following deficiencies: long training/ specification times; not guaranteed to work on all inputs; requires full connectivity.
Alternatively we discuss methods of using the topology and constraints of the problems themselves to design the topology and connections of the neural solution. We define several useful circuits-generalizations of the Winner-Take-All circuitthat allows us to incorporate constraints using feedback in a controlled manner. These circuits are proven to be stable, and to only converge on valid states. We use the Hopfield electronic model since this is close to an actual implementation. We also discuss methods for incorporating these circuits into larger systems, neural and nonneural. By exploiting regularities in our definition, we can construct efficient networks. To demonstrate the methods, we look to three problems from communications. We first discuss two applications to problems from circuit switching; finding routes in large multistage switches, and the call rearrangement problem. These show both, how we can use many neurons to build massively parallel machines, and how the Winner-Take-All circuits can simplify our designs.
Next we develop a solution to the contention arbitration problem of high-speed packet switches. We define a useful class of switching networks and then design a neural network to solve the contention arbitration problem for this class. Various aspects of the neural network/switch system are analyzed to measure the queueing performance of this method. Using the basic design, a feasible architecture for a large (1024-input) ATM packet switch is presented. Using the massive parallelism of neural networks, we can consider algorithms that were previously computationally unattainable. These now viable algorithms lead us to new perspectives on switch design.
Resumo:
Network information theory and channels with memory are two important but difficult frontiers of information theory. In this two-parted dissertation, we study these two areas, each comprising one part. For the first area we study the so-called entropy vectors via finite group theory, and the network codes constructed from finite groups. In particular, we identify the smallest finite group that violates the Ingleton inequality, an inequality respected by all linear network codes, but not satisfied by all entropy vectors. Based on the analysis of this group we generalize it to several families of Ingleton-violating groups, which may be used to design good network codes. Regarding that aspect, we study the network codes constructed with finite groups, and especially show that linear network codes are embedded in the group network codes constructed with these Ingleton-violating families. Furthermore, such codes are strictly more powerful than linear network codes, as they are able to violate the Ingleton inequality while linear network codes cannot. For the second area, we study the impact of memory to the channel capacity through a novel communication system: the energy harvesting channel. Different from traditional communication systems, the transmitter of an energy harvesting channel is powered by an exogenous energy harvesting device and a finite-sized battery. As a consequence, each time the system can only transmit a symbol whose energy consumption is no more than the energy currently available. This new type of power supply introduces an unprecedented input constraint for the channel, which is random, instantaneous, and has memory. Furthermore, naturally, the energy harvesting process is observed causally at the transmitter, but no such information is provided to the receiver. Both of these features pose great challenges for the analysis of the channel capacity. In this work we use techniques from channels with side information, and finite state channels, to obtain lower and upper bounds of the energy harvesting channel. In particular, we study the stationarity and ergodicity conditions of a surrogate channel to compute and optimize the achievable rates for the original channel. In addition, for practical code design of the system we study the pairwise error probabilities of the input sequences.
Resumo:
This paper presents a novel architecture for optimizing the HTTP-based multimedia delivery in multi-user mobile networks. This proposal combines the usual client-driven dynamic adaptation scheme DASH-3GPP with network-assisted adaptation capabilities, in order to maximize the overall Quality of Experience. The foundation of this combined adaptation scheme is based on two state of the art technologies. On one hand, adaptive HTTP streaming with multi-layer encoding allows efficient media delivery and improves the experienced media quality in highly dynamic channels. Additionally, it enables the possibility to implement network-level adaptations for better coping with multi-user scenarios. On the other hand, mobile edge computing facilitates the deployment of mobile services close to the user. This approach brings new possibilities in modern and future mobile networks, such as close to zero delays and awareness of the radio status. The proposal in this paper introduces a novel element, denoted as Mobile Edge-DASH Adaptation Function, which combines all these advantages to support efficient media delivery in mobile multi-user scenarios. Furthermore, we evaluate the performance enhancements of this content- and user context-aware scheme through simulations of a mobile multimedia scenario.
Resumo:
Large digital chips use a significant amount of energy to broadcast a low-skew, multigigahertz clock to millions of latches located throughout the chip. Every clock cycle, the large aggregate capacitance of the clock network is charged from the supply and then discharged to ground. Instead of wasting this stored energy, it is possible to recycle the energy by controlling its delivery to another part of the chip using an on-chip dc-dc converter. The clock driver and switching converter circuits share many compatible characteristics that allow them to be merged into a single design and fully integrated on-chip. Our buck converter prototype, manufactured in 90-nm CMOS, provides a proof-of-concept that clock network energy can be recycled to other parts of the chip, thus lowering overall energy consumption. It also confirms that monolithic multigigahertz switching converters utilizing zero-voltage switching can be implemented in deep-submicrometer CMOS. With multigigahertz operation, fully integrated inductors and capacitors use a small amount of chip area with low losses. Combining the clock driver with the power converter can share the large MOSFET drivers necessary as well as being energy and space efficient. We present an analysis of the losses which we confirm by experimentally comparing the merged circuit with a conventional clock driver. © 2012 IEEE.