2 parts : my work , our workIn my work, path loss, clustering and ids.Our work : evolution of better path loss model, placelife, case study.
In general, self powered nodes. That sense and gather info.How do they communicate?....multihop? With an end goal to send data to BS.Main area of focus: Body sensors in Hoslpitals, large sport fields and industrial automation
It is very obvious that wsns have a wide spectrumof applications. From Homeautomation: to Tracking the object. (logistics)Home automation : temp, smoke, fire alarm, turning on lights, ac, heating, windows open close, tv, etc….Intelligent Structural Health Monitoring System( Monitor mechanical stress after earthquakes…bridges…)Monitoring health conditionsof a patient in hospitals…(BAN)
Some more details……BP oil disater on the coast of mexico, 2 yrs ago! 4.9 million gallons of oil. And Damage to wildlife habitat.
Cracks on the walls, bridges and health of the heritage buildings can be monitored,2006, Bri-Mon is on its way!! For 120000 bridges.
Recent studies have also considered the monitoring and evaluation of the path loss caused by environmental factors
One solution put forward by the researchers to save energy is CLUSTERING.
Due to inherent complexity and diverse nature of WSNs (topology, channel characteristics, density), Analytical methods become inappropriate due to certain simplifications, which may lead to inaccurate results.Experimental studies- not practical : difficulties in deploying of real systems.(10s or 100s of nodes), programing and monitoring them in physical environment. Costly instrumentation etc…And we all know that in benchmarking, the results in many cases cannot be extrapolated to suit the changes in the system or environmentHence, testing & performance evaluation of WSNs through analytical modelling, real deployment and test beds can become complex, inaccurate, time consuming and costly.We opt for simulators.
A generic framework supporting development of wsns.Data from SA model, Positioning model and Path loss modesl are fed as input to the simulation framework (castalia) to find the performance parameters, life time and then by reconfiguring, v can find out the optimum results.I Wil not go very depth in to this now, but later in our present work we give more details.
Reduction in tx signal strength as a function of distance, considering freq.When path loss is not considered, therefore the retransmission caused are also ignored. Hence it becomes too optimistic.There fore, we must consider path loss for more realistic evaluation.
Consider fire alarm system. Temp and smoke detectors are distributed inside the building, with 5 areas, (5 rooms) and different obstacles/objects with diff attenuationsT is temp, sm is smoke, sp is sprinlerwhen t sensor reads a value higher than threshold, sends a mesh to smoke to verify smoke. If smoke, sprinkler is activated.Also, a Central heating system: t every 30 sec.we consider indoor environment and the dependant path loss modelThe path loss behaviour is dependent on the distance between nodes and the attenuationfactor added by the objects.attenuation can vary based on construction materials and object size
Castalia provides a good low level simulation platformThe user provides the path loss related parameters
It is clearly evident that the lifetime of the nodes is heavily dependent on the impact of the path loss, Node 3 consumes 13 joules of more energy due to path loss, when compared toThe case when there is no path loss.Because of the retransmissions, more energy is consumed by the nodes
If nodes are separated by a large distance, they cannot communicate directly due to transmission range.However, in MULTHOP Communications there exits HOT SPOT problems.!!!!!!!
When the load balancing id ineffective, HOTSPOT problem exists!
To mitigate hot spot problem,
The further a cluster head is located from the BS, the larger its competition radius reduce intra-cluster traffic and hence can handle more relay trafficHow to calculate the size of the clusters.
C is environment dependant constant coefficient specified by the application.
For WSNs, while the IDS enhances security, it can shorten the lifetime of the WSN since the IDS may require to run in promiscuous mode .More precisely in promiscuous mode, each IDS can continuously eavesdrop the radio in order to check the correct behaviour of all other nodes.Hence, a need for new approach, the agreement based IDS can be improved further…..We consider both these cases and run our experiments.
The by. general's problem describes a problem where 1 commander and n-1 lieutenant's communicate with each other.It is an abstraction of the problem of reaching an agreement in a system where the nodes may exhibit arbitrary behaviour. (say a node sends faulty data)Lamppost and dole introduced algorithms (oral messages and signed messages algorithms) to overcome this problem,How ever, the number of messages exchanged is very large.And boos of the energy limitations in wans, such solutions would prove very expensive in terms of both number of messages and time.So, we tried to find out how expensive it would prove, if such a problem arise in wans.
To cope up wth m traitors, lamport proposed a solutipon that works for 3m+1 or more leiutanants. Each commander sends an order/value to n - 1 lieutenants. And based on obtain the same value majority of times, the leuitanant decides what to do!
Case study considered is a home automtionsystm. (fire alarm system, composed of various temp and smoke sensors, connected to an actuator to sprinkle wate in case of fire)When temp sensor reads a value exceeding the threshold, it sends mesg to smoke detector to check for smoke. If yes, then actuator is activated for water.We run the experiment for 3 cases.Fire alarm system with out any idsFire alarm system based on byzantine oral message soultionFire alarm system in which the ids is distributed on each node and runs in promiscuous mode.We use castalia simulation package.
to check cost of two different intrusion detection systems (watch dog, byzantine oral solution)Results presented are given up for up to 100 nodes60% of the nodes are temperature sensors, 30% for smoke and 10% are sprinkler actuatorsResults show that the energy consumed coz of byzantine oralmesg solution increases as the number of nodes increase.Also, if we consider only 10 nodes, the avg delay for round trip time is 40ms
We propose a generic frame work that supports the development of wsns. It is generic as it is independent from programing languages, hardware, and neteorkr topology independent.Architecturing modeling frame work is used to model behaviour of each kind of node and how it interacts with other nodes.Env modeling framework is used to model the phy environment where the application is deployed in, The main aim is to create a realistic representation of the env, of the application.Code genrtation frame work will manage the repositories of code generation enginesAnalysis framework is very similar to code generation one but is in charge in managing analysis engines for wsn,like coverage, connectivity , energy etc,
In our approach, model driven techniques are used to modlsoftwr and hardwr architecture of wsn nodes. We have the main building blocks.Behavioural description of events, conditions, actions etc which together describes the control flow with in the components from abstract point of view.From our case study, ie home automation Conditions and actions such as tem threshold, smoke sensing, activating sprinkler etc….Tmp>40,Smoke ?Sprinlr on?
For low level detailsof each type of node….Os such as tinyos, contokietc can be used. MAC protocols such as smac, tmac, 802154, tunable mac etcRoutin protocols such as bypass and multipathRadio parameters, energy source details etc can be specified. For our case study…….tmac, 3aa, multipath routing etc….
Designer can specify physical env..2d or 3d. Rep of env. And also the obstacles can be placed.For our case study, we consider a home auto mation system with 5 rooms ,….various obstacles etc…. With diff attenuation factors.
Mapml and depml are weaving models. For mapping Saml and nodeml…..mapml..This approach provides a clear separation between software components, wsn nodes and phyenv,promoting the reuse of models.
Its a transformation tool which allows developers to automatically obtain Castalia simulation scripts from our modeling languagesPlacelife lends itself as a flexible and efficient tool which provides a more realistic approach for analysing WSNs and evaluating the performance in terms of energy efficiencyPlace life is our tool, part of our mde, model driven engine.Using graphical Editor: environment editor allows to specify physical envi. (Includes diff. sensors, diff obstacles)App model defines behaviour of node. From this…. Transmission and sensing rates can be derived.Other layer info such as network, data and physical layer.Obstacles and sensor position together computes the pathloss.We feed it to the simulator.
Pr: The received signal powerPt: The transmited signal powerK: Pathloss factor calculate using the second formula: Path loss exponent, take from the tables for 2.4 GHz which is 4-6 for our cased0:is typically 1-10m indoors 10-100m outdoors we will use indoors
In general health care systems, like in NHS UK, we have the following scenario, where data acquisition take splace using these meters and labs.Then , we have interpretation using the reports And then a descision is made by the expert.
Instead, using WSNs, we can do this easily with out any delays and mistakes of humans !!!
Presentation l`aquila new
Senso LABSENSO LAB is one of the most advanced wireless sensornetwork labs., hosting hundreds of heterogeneous motes thatare deployed around Middlesex University.More than 20 members Prof Orhan Gemikonakli Dr Enver Ever Dr Leonardo Mostarda Krishna Doddapaneniwww.eis.mdx.ac.uk/staffpages/leonardom/WSN/index.php
ENERGY AWARE PERFORMANCE EVALUATION OF WSNS Krishna Doddapaneni Krishna Doddapaneni School of Science and Technology School of Engineering and Information Sciences
What are they and where are they used • A large number of small-sensing self-powered nodes gathering information • Communicating in a wireless fashion with an end-goal to hand their processed data to a base-station • Key elements: Sensing, Processing & Communication • Main area of focus - Body Sensors (Hospitals), Bio-Medical, Large- Scale Sport Fields, Industrial Automation
Oil spills• Gulf oil spill• No monitoring (use of faulty concrete plugs)• Mesh-based wireless sensor networks for constant monitoring of the rigs• Nigerian government funding • WSN for monitoring oil spills • The project went through several stages • The notification is in November • Equipment-provided
and more…• Bridge Monitoring• In California, 13% of the 23,000 bridges have been deemed structurally deficient, while 12% of the nations 600,000 bridges share the same rating• Structural health monitoring (SHM) is a sensor-based pre-emptive approach• New York may be the first state with a 24/7 wireless bridge monitoring system• Another application in India: Bri-Mon (Monitoring Railway bridges)
Crucial Factors• Life time of sensor node:1. Microprocessor2. Sensing module3. Wireless transmitter/receiver.Existing studies consider these modules for best deployment, topology,protocol selection, etc.
Energy consumption in a sensor node can be attributed to either “useful” or “wasteful” sources.Useful energy consumption: Wasteful energy consumption:• Transmitting/receiving data. • Idle listening.• Processing query requests. • Retransmissions.• Forwarding queries/ data to • Overhearing. neighbouring nodes. • Generating/handling control packets.
Path loss• Attenuation in power density of an electromagnetic wave as it propagates.• Path loss is effected by free-space loss, refraction, diffraction, reflection, coupling loss, absorption, propagation medium…..• Path loss effects should be considered for a more realistic evaluation
Simulation Path loss calculation Where, Lp is path loss between 2 points Lo is path loss in Open space mtype is number of objects of same type wtype is loss in decibels attributed to that object d is distance between the points
Clustering• Achieve high energy efficiency Why clustering• Increase the network scalability• Each cluster has a coordinator(CH) & number of nodes• Nodes only communicate to their CH.• Data aggregation, rotation of CH Advantages• Distribution of load across all nodes Member node Cluster head CH
Multihop Communication • Data travels from the source to the destination node via more than two hops. • Increase the range of the network by a significant margin Thank you ! b c a d
Uniformly distributed It is ineffective to balance loads among cluster heads to avoid hot spots problem, if the cluster heads are uniformly distributed, like in HEED.
Unequal clustering algorithm (UHEED) • Clustering, Multihop Communication, • Mitigates Hotspots ! • UHEED combine HEED and EEUC • The leader election is performed according to HEED • The radius size is calculated according to EEUC • Improves network life time.
UHEED mechanism• Unequal sized clusters are based on the distance from a cluster head to the base station and energy level.• The further a cluster head is located from the BS, the larger its competition radius is, and hence the size of the cluster.• Unequal sized clusters reduce intra-cluster traffic for CH nearer to BS.
Competition radiusWhere, is maximum competition radius, predefined. and are max. and min. distances. C is constant coefficient between 0 and 1. The life time of CH closer to BS is more critical, the clusters further away have larger sizes compared to closer ones.
IDS in WSN Enhances security- Watchdog - Agreement Based- Promiscuous mode – radio - Monitoring based on pre- continuously on, to check the defined agreement. correct behaviour of other nodes. - Byzantine oral solution/ signed messages algorithms.- Hence, lifetime decreases. - It is also expensive in terms- Not really suitable for of no of messages sent and eventtriggered sensing. time.Hence, a need for new approaches, improve Agreement based IDS
The Byzantine Generals Problem Attack! No, wait! Surrender! Wait… Attack! Attack! Wait…
PlaceLifeSoftware Architecture Modelling Language• Set of components that exchange messages• Components have variables manipulated by the behaviour• Behaviour is represented by a list of events, conditions and actions
PlaceLifeEnvironment Modelling Language• The physical environment in which the WSN nodes are deployed• Obstacles, material….
PlaceLifeWeaving models • Mapping Modelling Language • Deployment Modelling LanguageThis approach provides a clear separation between software components, WSNnodes and the physical environments, thus promoting the reuse of models.
Present work!• Expressiveness of Languages : Precision of our abstraction• Improvise the path loss model The one we used in our earlier workNow, Where,
Path loss data• With the formula, we calculate the path loss between two nodes.• With this data, we explicitly set our path loss map. (its like a matrix, representing the path loss values between the nodes on the network).• This is done through the SN.wirelessChannel.pathLossMapFile parameter, in Castalia• Example : 0>1:56,2:40,3:59,4:54,5:58• This means that when node 0 is transmitting, node 1 is experiencing 56dB path loss, node 2 is experiencing 40dB loss, node 3 a 59dBm loss, etc.
Future work: optimal deployment Smoke Sprinkler Smoke Temp Temp Smoke Temp Sprinkler• Which one is the optimum deployment to improve the network lifetime?
Future work: optimal deployment Smoke Sprinkler Smoke Temp Temp Smoke Temp Sprinkler• Here we avoid obstacles but nodes must act as routes
Castalia A simulator for Wireless Sensor Networks and Body Area Networks, Partly enabled by OMNeT++For Testing Distributed algorithms, Protocols @ realistic nodebehaviour, especially relating to access the radio.Main features include : Advanced channel model Advanced radio model Extended sensing modelling provisions Node clock drift MAC and routing protocols available. Designed for adaptation and expansion