Network Management for Wireless Sensor Networks

Zena Mohammed

Network Management Requirements

Example of Management Architecture: MANNA

Other Issues Related to Network Management

• Naming

• Localization

OutlineIntroduction

Traditional Network Management Models

Network Management Design Issues

• Network management is the process of managing, monitoring, and controlling the behavior of a network.

• Wireless sensor networks (WSNs) pose unique challenges for network management that make traditional network management techniques impractical.

• A network management system designed for WSNs should provide a set of management functions that integrate configuration, operation, administration, security, and maintenance of all elements and services of a sensor network

Introduction

PhysicalData LinkNetworkTransportApplication

A computer communication network generally consists of three components:

o Physical devices

• Links (wireless or wired link),

• Network nodes (hub, bridge, switch, or router), and

• Terminals and Servers;

o Protocol; and

o Information that is being carried, including applications.

The collaboration of physical devices and network protocols forms the underpinning support for the applications. However, the physical devices and protocols are not sufficient to support effective operation of a communications network; network management (NM) tools and techniques are also required to help provision network services and ensure cooperation of entities in the network.

Network Management Requirements

the reasons for management functions are manifold and may be summarized as follows:

1. There are many heterogeneous devices and software entities that comprise the network, and some may fail.

2. Optimization of system performance as a distributed system require NM to collaborate in the process.

3. For most networks, NM functions can be used to gather and analyze the behavior of user interaction during network interface, which is very important in planning the long-term evolution of network capacity and its performance.

3.1Simple Network Management Protocol For managing networks, SNMP is broadly use today.

It includes three components: Network Management System (NMS), Managed Elements, and Agents.

Role of NMS :o NMS is a set of applications that monitor and/or control managed

elements. o NMS can request management information/attributes from the agent.o NMS present the results to NM users in figures/tables form.o NMS can also set attributes within the agent.

Traditional Network Management Models

Role of Managed Element :

o SNMP agents run on each managed element.

o The managed elements:

o Collect & Store management information in the MIB and

o Provide access through SNMP to the MIBs.

managed elements include: Routers, Switches, Servers, and Hosts.

Advantages of SNMP:

o Its very simple and widely deployment.

o In SNMP version 3 it can obtain more information by a pair of PDUs such as

(GetBulkRequest and GetResponse).

Disadvantages of SNMP :o It consumes considerable bandwidth since it often gets only one

piece of management information at a time: GetRequest (GetNextRequest) and GetResponse.

o Due to the usually large number of managed elements, large bandwidth consumption still exists.

o It only manages network elements; it does not support network-level management.

3.2 Telecom Operation Mapo It is based on the Service management Network management process models.

o TOM presents a model for telecommunications management for network and service

management and a view of ‘‘operations.’’

o IDEA: To introduce processes comprising operations and their automation.

o TOM only provides a framework for service management.

Levels / Layers

o Horizontally Layers for service management

o Service Fulfilment,

o Service Assurance, and

o Service Billing.

o Vertical Layers for service management:

o Network and Systems Management,

o Service Development and Operations, and

o Customer Care Process.

• Several issues must be addressed carefully before designing network management tools for WSNs. To begin with, the management functions required for WSNs should first be identified

Basic Issues:o Power efficiency o Data centric o Data aggregationo Attribute-based Addressingo Locationing systems, ando External Networks

Network Management Design Issues

Which factors should be consider while designing a Network Management Protocol ?

o Management solutions should be energy efficient, using as little wireless bandwidth as possible since communication is highly energy demanding.o Management solutions should be scalable. This is especially important

since it future WSNs may consist of tens to thousands of nodes.

o Management solutions should be simple and practical since WSNs are resource-constrained distributed systems.o MIB for WSNs should contain a general information model for sensor nodes, features of WSNs, and WSN applications.o Management solutions for WSNs should provide a general interface

to the applications since applications can perform better when able to access management information.o Management solutions should be implementable as middleware.

WSN Communications Architecture

Sensor fieldSensor nodes

Internet

Sink

Manager Node

Sensing nodeSensor nodes can bedata originators anddata routers

• MANNA (a Management Architecture for Wireless Sensor Networks ) is a policy-based management system that collects dynamic management information , maps this into WSN models, and executes management functions and services based on WSN models.

MANNA defines the following managed object classes:

1. Network (information on network behavior and features such as data delivery model, network structure, and mobility)

2. Managed Elements(such as sensor nodes)3. Equipment (the physical components of sensor nodes)4. System (information on operating system)5. Environment (the environment the WSN is running),6. Phenomenon, and7. Connection.

. Example of Management Architecture: MANNA

MANNA lists several common management functions for WSNs: environment monitoring functions, a coverage area supervision function, a topology map discovery function, an energy-level discovery function, an energy map generation function, and several others.

It also provides a dynamic MIB model for WSNs: a sensing coverage area map, a communication coverage area map, a WSN behavior model, a node dependence model, network topology, residual energy, and so on.

In MANNA, the management functions have the lowest granularity and can be combined into management services.

Some examples of WSN models include: Topology map depicting node connectivity and reachability of the

network. Residual energy map showing battery level of nodes in the network. Sensing coverage area map describing the area covered by sensor

elements. Communication coverage area map presenting communication

range of nodes in a network. Audit map describing the security status of sensor nodes in a

network, whether nodes have been attacked.

There are several other issues related to sensor network management, the most important being o naming,o localization,o maintenance, ando fault tolerance.

. Other Issues Related to Network Management

Naming is the scheme used to identify a sensor node.

An efficient naming scheme can lower computation overhead and make routing

protocol energy efficient.

Localization schemes determine the location of sensor nodes since such

information is important for some sensor applications.

The maintenance issue may involve actions such as replacing batteries, keeping

connectivity, and configuring sensor nodes.

-The maintenance activity is used to maintain normal operation of the entire

network for as long as possible.

Several factors can cause faults in network operation, including hardware and

software error. Therefore, different schemes must be implemented to provide fault

tolerance.

4.1 NamingNaming is the scheme used to identify a sensor node. • An efficient naming scheme can lower computation overhead

and make routing protocol energy efficient.

There are two traditional approaches to naming:o low level: naming such as node addresses is typically

application independent but topology and location dependent

o high level: naming is usually application dependentand location independent.

High-level naming is built on the top of low-level naming.

4.2 Localization• Localization schemes determine the location of sensor

nodes since such information is important for some sensor applications.

Advantages of this knowledge are that :1. some applications, such as those for tracking of objects, are

highly location dependent2. location-based routing, which may also result in energy

conservation is enabled3. knowledge of location usually enhances security;4. locations are helpful for sensor network management and

monitoring

5. locations stimulate the creation of new applications6. sensor nodes that move can be controlled through knowledge of

their location and 7. for applications with low-level naming and/or data-centric WSNs,

knowledge of location information is absolutely necessary.

• Localization classification

Localization Algorithm

Centralized Schemes Distributed Schemes

Range-free SchemesRange-based Scheme

o Centralized Scheme

o In this scheme Sensor nodes send control messages to a central node whose

location is known.

o The central node then computes the location of every sensor node and informs

the nodes of their locations.

o Distributed Scheme

o Each sensor node determines its own location independently.

o The distributed localization can be further grouped into:

o Range-based schemes and

o Range-free schemes.

o In the range-based approach, some range information, such as time of arrival,

angle of arrival, or time difference of arrival is required.

o The range-free algorithms works as follows:

o Several seed nodes are distributed in WSNs.

o Seed nodes know their own locations, and they periodically broadcast a control

message with their location information.

o Sensor nodes that receive these control messages can then estimate their own

locations.

CLUSTERING IN WSN

• Clusters: grouping of sensors that performing similar tasks are known as clusters.

• Hierarchical clustering is the efficient way to utilize the energy in an efficient manner.

• In hierarchical cluster, it contains Cluster Head, Regular Nodes and Base Station.

• After the cluster head is selected, it collects the data from all of its member nodes and aggregates it in order to eliminate the redundancy. Thus it limits the amount of data transmission to Base Station, hence remaining energy level is increased and network lifetime is maximized.

• the optimal number of cluster head that would lead to minimize the average energy spends in the network for each round.

Cluster-head Election using Fuzzy Logic for Wireless Sensor Networks

• Cluster Head (CH) election is the process to select a node within the cluster as a leader node. A CH is responsible for not only the general request but also assisting the general nodes to route the sensed data to the target nodes.

• A Fuzzy Logic approach to cluster-head election is proposed based on four descriptors:– remain energy - energy level available in each node– concentration - number of nodes present in the local distance r

vicinity– centrality- a value which classifies the nodes based the energy

concentration on cluster heads is distributed.– neighbor distance -the sum of distances between the node and the

nodes which is within r distance

Fuzzy c-means algorithm: the fuzzy c-means (FCM) algorithm is one of the most widely used methods in fuzzy clustering.• An extension of k-means• Hierarchical, k-means generates partitions– each data point can only be assigned in one cluster

• Fuzzy c-means allows data points to be assigned into more than one cluster– each data point has a degree of membership (or probability) of

belonging to each cluster

Fuzzy C Means Algorithm

Worked out Example

• Input: Number of Objects = 6 Number of clusters = 2

X Y C1 C2

1 6 0.8 0.2

2 5 0.9 0.1

3 8 0.7 0.3

4 4 0.3 0.7

5 7 0.5 0.5

6 9 0.2 0.8

Cluster 1 Cluster 2

Datapoint Distance Datapoint Distance

(1,6) 1.40 (1,6) 3.88

(2,5) 1.17 (2,5) 3.32

(3,8) 1.99 (3,8) 2.16

(4,4) 2.64 (4,4) 2.91

(5,7) 2.75 (5,7) 0.28

(6,9) 4.62 (6,9) 2.50

• Now the New Membership value is

Step 5 : Now continue this process until get the same centroids.

X Y C1 C2

1 6 0.7 0.3

2 5 0.6 0.4

3 8 0.5 0.5

4 4 0.5 0.5

5 7 0.1 0.9

6 9 0.3 0.7

Dynamic Topology

Node mobility has a great effect on the designing of routing protocols

Node mobility creates a dynamic topology, i.e., changes in the connectivity between the nodes

Mobility in Ad Hoc Networks

Dynamic Routing

Route Maintenance

• .

A node senses something “interesting”Neighbor sends a REQ listing all of the data it would like to acquireSensor broadcasts dataNeighbors aggregate data and broadcast(advertise) meta-data

SPIN-BCThe process repeats itself across the network

DATAREQADV

It sends meta-data to neighbors

• . SPIN-BC

I am tired I need to sleep …

Advertise meta-data

Request data

Send dataAdvertise

Advertise

Nodes do need not to participate in the process

Request data

Send data

Send data

Advertise meta-data

Request data

Send data

Gradient represents both direction towards data matching and status of demand with desired update rateProbability 1/energy costThe choice of path is made locally at every node for

every packetUses application-aware communication primitives

expressed in terms of named dataConsumer of data initiates interest in data with certain

attributesNodes diffuse the interest towards producers via a

sequence of local interactionsThis process sets up gradients in the network to draw

events matching the interestCollect energy metrics along the wayEvery route has a probability of being chosen

Directed Diffusion

Sink

Source

Four-leggedanimal

Reinforcement and negative reinforcement used to converge to efficient distribution

Has built-in tolerance to nodes moving out of range or dying

Directed Diffusion

Source

Sink

Some Applications of WSNsBattlefield

Detection, classification and trackingExamples: AWAIRS (UCLA & Rockwell Science Center)

Examples:ZebraNet (Princeton)

Seabird monitoring in Maine’s Great Duck Island (Berkeley & Intel)

Habitat Monitoring Micro-climate and wildlife monitoring

Some Applications of WSNs

Structural, seismic

Bridges, highways, buildingsExamples: Coronado Bridge San Diego (UCSD), Factory Building (UCLA)

Smart roadsTraffic monitoring, accident detection, recovery assistanceExamples: ATON project (UCSD)

highway

camera microphone

Contaminants detection Examples: Multipurpose Sensor Program (Boise State University)