chapter 4: cooperation in wireless ad- hoc and sensor networks j. barbancho, d. cascado, j. l....

CHAPTER 4:Cooperation in Wireless Ad-Hoc and Sensor Networks

J. Barbancho, D. Cascado, J. L. Sevillano, C. León, A. Linares and F. J. Molina

In M. S. Obaidat and S. Misra (Eds.) Cooperative Networking (Wiley)

1.Introduction

• Characteristics of a Wireless Ad-Hoc Sensor Network (WAdSN)– Nodes with tiny size, limited radio range, low

resources and autonomy, etc. – Different roles: data source, data sink and gateway.

• Cooperation in WAdSN: two paradigms– Data transport paradigm: Cooperation limited to an

exchange of information. – Cooperative paradigm: cooperation understood as a

distributed way to achieve an objective

2. Cooperation in WAdSN: Synchronization, Localization and Calibration

Important issues in WAdSN:• Time synchronization reduces energy waste

– Avoids collisions through reservation and scheduling– Avoids idle listening switching off the radio during the inactive

periods– Facilitates cooperation and data fusion (time stamping)

• Localization:– Allows location stamping of sensed data– Facilitates data aggregation (e.g. sensors in the same area)

• Calibration: – Needed to combine data from several sensors

2. Cooperation in WAdSN: Synchronization, Localization and Calibration

SLC (Synchronization/Localization/Calibration): concepts closely related to each other:

• Calibration: mapping the output of a sensor to a well-defined scale.

• Time synchronization: special case considering the hardware clock as the sensor.

• Localization:– RRS (Receiver Signal Strength) requires calibration of the

receivers– TDoA (Time Difference of Arrivals) requires time synchronization

• SLC should be performed periodically, specially in WAdSN

2. Cooperation in WAdSN: Synchronization, Localization and Calibration

SLC share similar techniques/classes:• External vs. Internal

– External: provides absolute SLC information– Internal: only relative information

• Continuous vs. On demand– Continuous: maintain SLC at all times– On demand: only during active periods. Can be event or time

triggered.

• Master-slave vs. Peer to peer– Master-slave: masters are reference nodes while slaves

estimate their SLC with respect to the masters– Peer to peer: reference nodes are not required

2. Cooperation in WAdSN: Routing

• Routing requires cooperation among nodes, specially in WAdSN (ad-hoc deployment, lack of global addressing, etc.)

• Some methods are based on the introduction of Artificial Intelligence techniques

• A directed graph is used to represent the communication links among all nodes (Network Backbone Formation)

• QoS parameters are used to dynamically select the routing path

2. Cooperation in WAdSN: Routing

Example: Sensor Intelligence Routing (SIR) Network Backbone Formation

wij: weight. V := {r, vi}i and T := V −{r}. d(vi): distance from the base station r to a node vi

p(vj): subset of nodes which are predecessors or successors of node vj. p: path from the root node to vj

2. Cooperation in WAdSN: Data Aggregation and Fusion

• Data Fusion reduces the number of packets transmitted, and therefore power consumption

• Additionally, it allows selecting routes with better energy and bandwidth efficiency:– Address-centric routing (a)– Data-centric routing (b)

2. Cooperation in WAdSN: Data Aggregation and Fusion

Data Fusion can be described by means of the Joint Directors of Laboratories (JDL) model:

• Level 0: Source preprocessing. • Level 1: Object refinement. • Level 2: Situation refinement. • Level 3: Impact assessment. • Level 4: Process refinement. • Level 5: Cognitive refinement.

2. Cooperation in WAdSN: Data Aggregation and Fusion

Example application: WAdSN to estimate water level in flood zones of the National Park of Doñana. A Self-Organized Map (SOM) is executed in every node,

trained with historical data.

• Level 0: The SOM receives data from environmental sensors

• Level 1: State of the water level is identified

• Level 2: Data aggregators

• Level 3:

• Level 4:

• Level 5: Biologists interpret the results at the Doñana Biological Station

Only changes in the state (water level) are sent

3. Research lines for WAdSN: Introduction

• A WAdSN is difficult to manage with devices only implementing MAC & PHY.– Synchronization, calibration, location…

• Upper layers are a good place to implement these strategies.– Middleware– Multi-agent systems– Artificial neural networks

3. Research lines for WAdSN: Middleware

• Heterogeneity is a problem for WAdSN nodes, leads to incompatibility:– Different hardware, OpSys, Network…

• Solution: an abstraction layer between OpSys and hardware: middleware.– Common interface for client/server communication– Service discovering– Service description– Common language to write applications

3. Research lines for WAdSN: Middleware

Architectures:• Distributed tuples:

L2IMBO, LINDA • Remote procedure call:

Java Remote Method Invocation, Modula-3, XML-RPC, .NET Remoting

• Message-oriented: Advanced Message Queuing Protocol, Java Message Service

• Object request broker: DCOM, CORBA, COM

3. Research lines for WAdSN: Middleware

• Middleware is a solution designed for large distributed system. Why to use it?

• In WadSN, resources are very limited. • Design principles for WAdSN middleware must

consider:– Distributed by nature. – Limited by low machine resources. – Focused on energy saving. – Dynamic availability and quality of data collected from

the environment. – Constrained applications quality of services.

3. Research lines for WAdSN: Middleware

Design principles:• Data-centric• Distributed and collaborative algorithms • Support of data aggregation • Lightweight • Cluster based architecture• Virtual-machine abstraction and • Common language to write applicationsExamples:• Cougar, SINA. AutoSec, DSWare, Impala, Milan, Mires, COCADrawbacks:• No solid functionality, no support to time and location in

measurements,

3. Research lines for WAdSN: Multi-Agent Systems

• Agent: is an entity located in one environment, capable of performing flexible and autonomous actions to achieve its goals.

• Agents reside in the WAdSN nodes:– Gathering information– Taking actions based on

collected information– Interact with other agents– Move to other sensors if

required

3. Research lines for WAdSN: Multi-Agent Systems

Agents are supported by a middleware architecture in order to take access to:

• Local services of the platform• Agent discovery and maintenance

– Agent=code + data + state + meta-information. • Common language to develop agents• Reactivity to changes• Asynchronous operation• Autonomy about their own actions• Communications with other agents• Collaboration and cooperation with other agents• Mobility to migrate between nodesExamples• IMPALA, Agilla, MASIF.

3. Research lines for WAdSN: Artificial Neural Networks (ANN)

ANN can be used …• When no algorithm exists to solve a specific

task, but the solution can be expressed on the basis of a rich set of input examples.

• For classification• For pattern recognitionFeatures of ANN• Robustness against noise• Easy to parallelize and distribute• Lightweight

3. Research lines for WAdSN: Artificial Neural Networks (ANN)

• Artificial Neuron: is an entity whose output is defined as a function of a set of weighted inputs – This output can be codified as a number within a

range or as a series of spikes distributed in time

3. Research lines for WAdSN: Artificial Neural Networks (ANN)

Neurons are arranged in layers

• Feed-fordward ANN• Recurrent ANNTraining before

operation (simple and fast algorithm)

• Supervised• Not supervised• Reinforcement

3. Research lines for WAdSN: Artificial Neural Networks (ANN)

• How can an ANN be implemented in a WAdSN? • One node, one neuron

– Nodes serve as input layer of the network. Further layers can be implemented in another place

– Suitable for pattern recognition, classification, or predictions

• One node, one ANN– Each ANN trained to solve an specific problem of the

WAdSN– Suitable for routing optimization, self-calibration,

insertion of new nodes.

4. Final Remarks• Cooperation in WAdSN is a collaborative action

between network nodes– Implemented in upper layers of OSI model

• Basic services for cooperation– Synchronization, localization and calibration

• Middleware makes cooperation easier– Cooperation implemented regardless hardware of

network technology– Multi-agent systems are a evolution of middleware– Designed to large systems. Difficult to implement in

WAdSN yet.