mohamed hauter cmpe 259 – sensor networks ucsc 1

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Mohamed Hauter

CMPE 259 – Sensor Networks

UCSC

Energy Management

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Outline

*Introduction

*Objectives

*Proposals and approaches

*Related Work

*Simulations and Results

*Strengths and weaknesses

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Paper 1:An Energy-Efficient Dynamic Power

Management in Wireless Sensor Networks

* An energy-efficient sensor network

*Minimal number of sensor nodes in active mode

*Increase the lifetime of the sensor network

*Prevent connection degradation

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Dynamic Power Management (Cont.)

*Terminology:

*DPM: Dynamic Power Management

*OGDC: Optimal Geographical Density Control

*ACPI: Advanced Configuration and Power Interface

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*Approach:

*Tackle energy efficiency on all levels of the entire network

*Dynamic power management = shutting down nodes when not needed and wake them up when necessary

*Consideration of the state of components ( microprocessor, A/D converter, memory, transceiver, etc.) when making a decision to turn off a node

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*Approach (continue):

*Density control while maintaining:a. Coverage

b. Connectivity

*Localized density control algorithm

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Dynamic Power Management (Cont.)*Approach (continue):

*Consideration of battery status and energy wasted in the process of node-awakening

*Incorporate OGDC in the control logic

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Related Work

*Verity of DPM techniques

*Dynamic Voltage Scaling

*Dynamic Voltage and Frequency Scaling

*Sentry based power management (application driven)

*Software and operating system power management

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Related Work (continues)

*Weaknesses of traditional predictive techniques:

*Cannot provide an accurate tradeoff between energy saving and performance degradation

*Does not deal with systems in which requests can be queued

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*Power aware sensor node model:

*Node components: processor, memory, AD converter, and transceiver (radio)

*Components of each node can be in different states: active, idle, or sleep

*Different combinations of component power modes

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*Sleep-state transition policy:

*P = Power Consumption

*t = Time of event

*s = sleep state

*Tau = transition mode

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*System Parameters:

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Simulations*50x50 meters area of coverage

*100 nodes

*Uniformly and randomly distributed

*Nodes are capable of directly communicating with the host

*Each node’s initial energy is 100 joules

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Results

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Strengths: * An energy-efficient sensor network * Minimal number of sensor nodes in active mode * Increase the lifetime of the sensor network * Prevent connection degradation

Weaknesses: *Analysis did not take latency into account * Events missed during deepest-sleep state * OGDC requires knowledge of node’s location (extra processing and memory overhead)

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Paper 2:Wireless Sensor Networks with Energy

Harvesting Technologies

* Utilize natural sources of energy (solar, motion, vibration, etc.) to recharge nodes’ batteries

*Employ energy-saving mechanisms

*Determine the sleep and wake up probabilities of nodes using a bargaining game

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Wireless Sensor Networks with Energy Harvesting Technologies

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Energy Harvesting Technologies

1. Solar 2. Thermoelectric

3. Vibration Based

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Buffers

Two types of buffers:

1.Local buffer: gathers data collected locally (through sensors).

2. External buffer: gathers data from other nodes to be relayed.

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Energy-Efficient Routing Protocol

To find the optimal path to deliver data packets while considering:

1. Energy level2. Path length3. Path reliability

Avoid:1. Idle listening2. Overhearing3. Packet collisions

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Energy-Efficient Routing Protocol (cont.)

• Using Explicit Signaling:• A node notifying the access point that it is going

into power-saving (PS) mode

• Dual Channel MAC Protocols (Avoid Collisions):• Signaling channel• Data transmission channel

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Energy-Efficient Packet Scheduling

• Lazy packet-scheduling scheme• Determine beginning and duration of transmission• Transmit at a low data rate• Save energy• Packet delay and reduced throughput

• Tradeoffs!

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Issues

• QoS vs. Energy Constrains

• Energy harvesting limitations

• Integration of energy harvesting techniques across layers

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Optimal sleep and wakeup strategy

• Radio modes:• Active – 25mW• Listen – 14mW• Sleep – 0.01mW

• Channel and queue-aware strategy• Radio - Listen when queue is empty• Sensor – sleep when channel quality is bad

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Bargaining Game

• Players: • Player 1: node• Player 2: data receiving entity

• Strategy:• Player 1: select wakeup probability when in sleep

mode• Player 2: select wakeup probability when in listen

mode• Payoff:

• Player 1: packet blocking probability• Player 2: packet dropping probability

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Bargaining Game

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Bargaining Game

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Bargaining Game

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Strengths: 1. Energy efficient 2. Incorporates the states of different components of the network

Weaknesses: 1. battery energy level is not taken into consideration when making a sleep/wakeup decisions 2. Data transmission delay – low data transmission rates 3. The assumption of one-hop routing model in which all nodes can reach the sink is not practical

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* Paper 3:A Low Energy and Adaptive Architecture for

Efficient Routing and Robust Mobility Management

in Wireless Sensor Networks

*Prolong the lifetime of the network

*Minimizing the data processing and communication costs

*Employ multi-hop communications effectively

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Hierarchical Adaptive and Reliable Routing Protocol (HARP)

Related Work

*LEACH: dividing the sensor network into cluster heads (CH) which can communicate with sinks and amongst themselves. Cluster Heads are constantly changing (random selection) to prevent draining its energy.

*SOP: a tree of cluster heads is built using fixed nodes.

*EDETA: builds a hierarchal tree among cluster heads to avoid direct communication with sink.

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How is HARP different? .

*HARP can save more energy by forming intra-cluster hierarchal architectures in conjunction with inter-cluster trees.

* Leverage node mobility to enhance network performance in terms of coverage, lifetime, energy efficiency, and latency.

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*Two hierarchal tree structure:1. Between CHs and the sinks

2. Within the cluster

*HARP has a local reconfiguration scheme in case of a failure

*Supports more than one sink - scalability

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HARP messages

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HARP phases

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LEACH clustering

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HARP clustering

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Failure Recovery Mechanisms

*Causes of failure:

*Battery depletion, node malfunction, multipath fading, low link quality, or node mobility.

*Mechanisms;1. The recovery slot

2. The substitute node

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s-HARP

*Unlike the LEACH approach, HARP ensures that nodes all die at the same time

*Solves the problem of the extra energy waste of CHs

*CHs are randomly selected, unless new node has less energy than existing CH.

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Results

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Results – wasted energy

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Results – total energy consumption

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s-HARP

*Strengths:

*Very high level of energy efficiency

*Scalable design

*Efficient Local recovery capability

*Optimizes routing of both upstream and downstream traffic flows

*Weakness:

*Increased complexity in terms of resource scheduling and network topology management

*Increased memory overhead

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*Questions ?

mohamed hauter cmpe 259 – sensor networks ucsc 1

Documents

energy efficient

nodes initial energy

employ energy

sensor sleep

energy packet delay

battery energy level

sleep mode player

minimal number of sensor