23 research outputs found
Improving energy efficiency in wireless sensor networks through scheduling and routing
This paper is about the wireless sensor network in environmental monitoring
applications. A Wireless Sensor Network consists of many sensor nodes and a
base station. The number and type of sensor nodes and the design protocols for
any wireless sensor network is application specific. The sensor data in this
application may be light intensity, temperature, pressure, humidity and their
variations .Clustering and routing are the two areas which are given more
attention in this paper.Comment: 7 Pages, 2 Figures and 1 Tabl
On the stability of flow-aware CSMA
We consider a wireless network where each flow (instead of each link) runs
its own CSMA (Carrier Sense Multiple Access) algorithm. Specifically, each flow
attempts to access the radio channel after some random time and transmits a
packet if the channel is sensed idle. We prove that, unlike the standard CSMA
algorithm, this simple distributed access scheme is optimal in the sense that
the network is stable for all traffic intensities in the capacity region of the
network
Feedback Allocation For OFDMA Systems With Slow Frequency-domain Scheduling
We study the problem of allocating limited feedback resources across multiple
users in an orthogonal-frequency-division-multiple-access downlink system with
slow frequency-domain scheduling. Many flavors of slow frequency-domain
scheduling (e.g., persistent scheduling, semi-persistent scheduling), that
adapt user-sub-band assignments on a slower time-scale, are being considered in
standards such as 3GPP Long-Term Evolution. In this paper, we develop a
feedback allocation algorithm that operates in conjunction with any arbitrary
slow frequency-domain scheduler with the goal of improving the throughput of
the system. Given a user-sub-band assignment chosen by the scheduler, the
feedback allocation algorithm involves solving a weighted sum-rate maximization
at each (slow) scheduling instant. We first develop an optimal
dynamic-programming-based algorithm to solve the feedback allocation problem
with pseudo-polynomial complexity in the number of users and in the total
feedback bit budget. We then propose two approximation algorithms with
complexity further reduced, for scenarios where the problem exhibits additional
structure.Comment: Accepted to IEEE Transactions on Signal Processin
Random Access Scheduling without Message Passing: A Collision-based AIMD Approach
Department of Computer EngineeringWireless scheduling has been extensively studied in the literature. Since Maximum Weighted Scheduling has been developed and shown to achieve the optimal performance, there have been many efforts to overcome its complexity issue. Random access has attracted much attention due to its potential for low complexity and distributed control, which are desirable for scheduling in multi-hop wireless networks. Although several interesting random access scheduling schemes have been shown to be provably efficient, they suffer in practice from high packet delays or severe performance degradation due to the control overhead to exchange information between neighboring links. In this paper, we develop a novel random access scheduling scheme that does not need message passing. We pay attention to the interplay between the links and control their access probabilities targeting at a certain collision rate. We employ the Additive Increase Multiplicative Decrease (AIMD) algorithm for convergence, and show that our proposed scheme can achieve the same performance bound as the previous random access schemes with high control overhead. We verify our results through simulations and show that our proposed scheme achieves the performance close to that of the centralized greedy algorithm.ope
EEGRA: Energy Efficient Geographic Routing Algorithms for Wireless Sensor Network
[[abstract]]Energy efficiency is critical in wireless sensor networks (WSN) for system reliability and deployment cost. The power consumption of the communication in multi-hop WSN is primarily decided by three factors: routing distance, signal
interference, and computation cost of routing. Several routing algorithms designed for energy efficiency or interference avoidance had been proposed. However, they are either too complex to be useful in practices or specialized for certain
WSN architectures. In this paper, we propose two energy efficient geographic routing algorithms (EEGRA) for wireless sensor networks, which are based on existing geographic routing algorithms and take all three factors into account.
The first algorithm combines the interference into the routing cost function, and uses it in the routing decision. The second algorithm transforms the problem into a constrained
optimization problem, and solves it by searching the optimal discretized interference level. We integrate four geographic routing algorithms: GOAFR+, Face Routing, GPSR, and RandHT, to both EEGRA algorithms and compare them with three other routing methods in terms of power consumption and computation cost for the grid and irregular sensor topologies. The results of our experiments show both algorithms conserve sensor’s routing energy 30% ~ 50% comparing to general geographic routing algorithms. In addition, the time complexity of EEGRA algorithms is similar to the geographic greedy routing methods, which is much faster than the optimal SINR-based algorithm.[[conferencetype]]國際[[conferencedate]]20121213~20121215[[iscallforpapers]]Y[[conferencelocation]]San Marcos, Texas, US
An Energy-Efficient Controller for Wirelessly-Powered Communication Networks
In a wirelessly-powered communication network (WPCN), an energy access point
(E-AP) supplies the energy needs of the network nodes through radio frequency
wave transmission, and the nodes store their received energy in their batteries
for possible data transmission. In this paper, we propose an online control
policy for energy transfer from the E-AP to the wireless nodes and for data
transfer among the nodes. With our proposed control policy, all data queues of
the nodes are stable, while the average energy consumption of the network is
shown to be within a bounded gap of the minimum energy required for stabilizing
the network. Our proposed policy is designed using a quadratic Lyapunov
function to capture the limitations on the energy consumption of the nodes
imposed by their battery levels. We show that under the proposed control
policy, the backlog level in the data queues and the stored energy level in the
batteries fluctuate in small intervals around some constant levels.
Consequently, by imposing negligible average data drop rate, the data buffer
size and the battery capacity of the nodes can be significantly reduced