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An Approach to Sensor Network Throughput Enhancement by PHY-
Aided MAC
Abstract:
Low power sensor networks with communication enabled by WiFi are
expected to be widely deployed. A major challenge is collecting event-
driven uplink data from a large number of low-power sensors with low
latency. In WiFi, the access point (AP) typically polls nodes individually to
schedule uplink transmission times, resulting in a large latency. In this
paper, we present a physical (PHY) layer-aided medium access control
(MAC) framework to enhance the uplink throughput of sensor data traffic.
In the approach, the acknowledgements from the sensor nodes to the poll
message are parallelized. By detecting the parallel acknowledgement, the
AP knows which nodes have data to send and allocates channel resources
by sending a pull message. This approach is referred to as the probe and
pull MAC (PPMAC) mechanism. Our scheme is based on maximizing the
achievable throughput of PPMAC by optimizing the PHY layer
components. More precisely, we investigate the parallel acknowledgement
detector design problem and develop a non-convex optimization
framework that maximizes the PPMAC throughput by optimizing the
parallel acknowledgement detection statistics. Numerical examples
illustrate that PPMAC outperforms the point coordination function (PCF)
and distributed coordination function (DCF) mechanisms, standardized in
IEEE 802.11, in terms of the achievable throughput and the overhead.
Existing System:
One common requirement in sensor network applications is the need to
support uplink sensor traffic with low latency. The key to attaining this
goal is to maximize the achievable uplink throughput.
However, sensor networks typically rely on battery-powered sensor nodes
and can not support many of the power-hungry, but throughput boosting,
operations commonly found in most wireless broadband systems.
In the absence of side information, the parallel acknowledgement detection
faces two major challenges: i) The design of a non-coherent, but robust,
parallel acknowledgement detector and ii) Adaptation to throughput
performance. The performance of the parallel acknowledgement detection
needs to be optimized so as to maximize the achievable throughput.
Proposed System:
The cross-layer optimized PPMAC is shown to outperform PCF and DCF.
Furthermore, PPMAC exhibits an excellent ability to adapt the channel
allocation to a wide spectrum of traffic conditions, making it suitable for
bursty sensor applications. We are not aware of similar work that treats
specific wireless access problems such as scheduling, medium assignment,
and throughput maximization as part of the parallel acknowledgement
optimization problem using discrete monotonic optimization tools.
Though we propose the framework to optimize the channel utilization for
wireless sensor networks, by being able to solve the optimization problem
formulated in the paper, we hope that our approach will inspire the use of
monotonic optimization techniques in other relatedwireless
communication problems.
Hardware Requirements:
• System : Pentium IV 2.4 GHz.
• Hard Disk : 40 GB.
• Floppy Drive : 1.44 Mb.
• Monitor : 15 VGA Colour.
• Mouse : Logitech.
• RAM : 256 Mb.
Software Requirements:
• Operating system : - Centos.
• Tool : - VM Ware Workstation
• Script : - NS2

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An approach to sensor network throughput enhancement by phy aided mac

  • 1. An Approach to Sensor Network Throughput Enhancement by PHY- Aided MAC Abstract: Low power sensor networks with communication enabled by WiFi are expected to be widely deployed. A major challenge is collecting event- driven uplink data from a large number of low-power sensors with low latency. In WiFi, the access point (AP) typically polls nodes individually to schedule uplink transmission times, resulting in a large latency. In this paper, we present a physical (PHY) layer-aided medium access control (MAC) framework to enhance the uplink throughput of sensor data traffic. In the approach, the acknowledgements from the sensor nodes to the poll message are parallelized. By detecting the parallel acknowledgement, the AP knows which nodes have data to send and allocates channel resources by sending a pull message. This approach is referred to as the probe and pull MAC (PPMAC) mechanism. Our scheme is based on maximizing the achievable throughput of PPMAC by optimizing the PHY layer components. More precisely, we investigate the parallel acknowledgement detector design problem and develop a non-convex optimization framework that maximizes the PPMAC throughput by optimizing the parallel acknowledgement detection statistics. Numerical examples illustrate that PPMAC outperforms the point coordination function (PCF)
  • 2. and distributed coordination function (DCF) mechanisms, standardized in IEEE 802.11, in terms of the achievable throughput and the overhead. Existing System: One common requirement in sensor network applications is the need to support uplink sensor traffic with low latency. The key to attaining this goal is to maximize the achievable uplink throughput. However, sensor networks typically rely on battery-powered sensor nodes and can not support many of the power-hungry, but throughput boosting, operations commonly found in most wireless broadband systems. In the absence of side information, the parallel acknowledgement detection faces two major challenges: i) The design of a non-coherent, but robust, parallel acknowledgement detector and ii) Adaptation to throughput performance. The performance of the parallel acknowledgement detection needs to be optimized so as to maximize the achievable throughput. Proposed System: The cross-layer optimized PPMAC is shown to outperform PCF and DCF. Furthermore, PPMAC exhibits an excellent ability to adapt the channel allocation to a wide spectrum of traffic conditions, making it suitable for bursty sensor applications. We are not aware of similar work that treats specific wireless access problems such as scheduling, medium assignment, and throughput maximization as part of the parallel acknowledgement optimization problem using discrete monotonic optimization tools.
  • 3. Though we propose the framework to optimize the channel utilization for wireless sensor networks, by being able to solve the optimization problem formulated in the paper, we hope that our approach will inspire the use of monotonic optimization techniques in other relatedwireless communication problems. Hardware Requirements: • System : Pentium IV 2.4 GHz. • Hard Disk : 40 GB. • Floppy Drive : 1.44 Mb. • Monitor : 15 VGA Colour. • Mouse : Logitech. • RAM : 256 Mb. Software Requirements: • Operating system : - Centos. • Tool : - VM Ware Workstation • Script : - NS2