Computational Intelligence Based Data    Aggregation Technique in Clustered WSN:         Prospects and Considerations     ...
Contents• Research Intention• Preparatory Concept• WSN network architecture and routing  protocols• Data aggregation and f...
Research Intention• Data aggregation in wireless sensor networks is a hot research  focus in recent times.• Data aggregati...
Research Intention• So better clustering of sensor nodes => better data  aggregation/fusions => better performance in WSN ...
Contents• Research Intention• Preparatory Concept• WSN network architecture and routing  protocols• Data aggregation and f...
Preparatory Concept• A sensor node consists of mainly 3 subsystems as follows.*sensor subsystem performs sensing function ...
Preparatory ConceptThe data aggregation usually involves the fusion of data from multiple sensors at intermediate  nodes a...
Contents• Research Intention• Preparatory Concept• WSN network architecture and routing  protocols• Data aggregation and f...
WSN network architecture and routing protocols• The network structures in WSN can be classified as flat  networks, hierarc...
WSN network architecture and routing protocols• The mobility based networks exploit mobility for data  collection in WSNs....
WSN network architecture and routing protocols• Multipath based networks                                                  ...
WSN network architecture and routing protocolsHeterogeneity based networks• A heterogeneous WSN consists of three types of...
WSN network architecture and routing protocols• Here the author summarized categories of routing protocols for  various se...
Contents• Research Intention• Preparatory Concept• WSN network architecture and routing  protocols• Data aggregation and f...
Data aggregation and fusion in WSN• In Data aggregation/collection process data from sensors in an area is  gathered (for ...
Data aggregation and fusion in WSN• The Data aggregation techniques include data centric and address centric  routing heur...
Data aggregation and fusion in WSN• In data fusion at a sensor node ,the data aggregated from multiple nodes is   processe...
Data aggregation and fusion in WSNdata fusion architecture:-•   In centralized architecture, the fusion process is perform...
Contents• Research Intention• Preparatory Concept• WSN network architecture and routing  protocols• Data aggregation and f...
Data aggregation protocols based on network architecture• The architecture of the network influences the performance of th...
Data aggregation protocols based on network architecture•   The data aggregation techniques designed for flat networks inc...
Data aggregation protocols based on network architectureHEED :- Hybrid Energy Efficient Distributed Clustering•   HEED was...
Contents• Research Intention• Preparatory Concept• WSN network architecture and routing  protocols• Data aggregation and f...
Computational intelligence and data aggregation in sensor networks• CI is defined as the computational models and tools of...
Computational intelligence and data aggregation in sensor networks• For fusion process neural networks are well suited bec...
Contents• Research Intention• Preparatory Concept• WSN network architecture and routing  protocols• Data aggregation and f...
Conclusion• Due to the several limitations of wireless sensor network, all  CI techniques can not be applied in the field ...
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Computational intelligence based data aggregation technique in clustered wsn

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Transcript of "Computational intelligence based data aggregation technique in clustered wsn"

  1. 1. Computational Intelligence Based Data Aggregation Technique in Clustered WSN: Prospects and Considerations Muhammad Umar FarooqProceedings of the World Congress on Engineering and Computer Science 2012 Vol II WCECS 2012, October 24-26, 2012, San Francisco, USA Keywords—Data Aggregation, Computational Intelligence, Clustering, Wireless Sensor Networks, Routing Reporter NILAMADHAB MISHRA D0121008
  2. 2. Contents• Research Intention• Preparatory Concept• WSN network architecture and routing protocols• Data aggregation and fusion in WSN• Data aggregation protocols based on network architecture• Computational intelligence and data aggregation in sensor networks• Conclusion 2
  3. 3. Research Intention• Data aggregation in wireless sensor networks is a hot research focus in recent times.• Data aggregation is defined as the process of aggregating the data from multiple sensors to eliminate redundant transmission and provide fused information to the base station.• The main goal of data-aggregation algorithms is to gather and aggregate data in an energy efficient manner so that network lifetime is enhanced.• The data aggregation helps to improve the performance of WSN routing protocol and further improves the overall performance of the sensor networks.• Hierarchical network or clustering plays vital role for data aggregation ,where sensor nodes are divided into groups and assigned various roles to each group. 3
  4. 4. Research Intention• So better clustering of sensor nodes => better data aggregation/fusions => better performance in WSN routing => better life time of sensor networks or better network longevity.• Hence in order to improve the efficiency of data aggregation technique , the author’s intentions to integrate the computational intelligence techniques with the conventional data aggregation techniques for making the solution non- conventional/non-traditional.• The computational intelligence techniques comprise artificial neural computing ,fuzzy computing ,evolutionary computing, swarm intelligence and their novel integrations.• Hence should use a novel hybridization of computational intelligence techniques for effective and efficient data aggregation. 4
  5. 5. Contents• Research Intention• Preparatory Concept• WSN network architecture and routing protocols• Data aggregation and fusion in WSN• Data aggregation protocols based on network architecture• Computational intelligence and data aggregation in sensor networks• Conclusion 5
  6. 6. Preparatory Concept• A sensor node consists of mainly 3 subsystems as follows.*sensor subsystem performs sensing function in the area where it is deployed.*processing subsystem performs obligatory computations at sensor node level.*communication subsystem disseminates the sensed data across the sensor networks.• The data dissemination from source to sink Usually requires the transit node positioning Information either through GPS-free localization or relative localization or absolute Localization techniques. 6
  7. 7. Preparatory ConceptThe data aggregation usually involves the fusion of data from multiple sensors at intermediate nodes and transmission of aggregate data to the sink or base station. The data aggregationattempts to collect the most critical data from sensors and make it available to the sink in low latency(potential) and energy efficient manner. So the data aggregation techniques can be used to combine several correlated data signals into a smaller set of information that maintains the effective data of the original signals. 7
  8. 8. Contents• Research Intention• Preparatory Concept• WSN network architecture and routing protocols• Data aggregation and fusion in WSN• Data aggregation protocols based on network architecture• Computational intelligence and data aggregation in sensor networks• Conclusion 8
  9. 9. WSN network architecture and routing protocols• The network structures in WSN can be classified as flat networks, hierarchical networks and location based networks and deal with routing differently.• For routing in a flat network, the nodes are same, have same capabilities and similar tasks.• In case of hierarchical networks, the sensor nodes are divided in groups called clusters.• In case of location based networks, the locations of the sensor nodes are used in calculating and selecting a route from source to the destination.• In a data-centric network, long-term storage (e.g. disk storage) of the data is also a part of the "network" and may serve requestors of that data in the future. 9
  10. 10. WSN network architecture and routing protocols• The mobility based networks exploit mobility for data collection in WSNs. It considers properties of sink mobility as well as the wireless communication methods for data transfer: Mobile base station (MBS)-based solutions:• An MBS is a mobile sink that changes its position during operation time. Data generated by sensors are relayed to MBS without long term buffering. Mobile data collector (MDC)-based solutions:• An MDC is a mobile sink that visits sensors. Data are buffered at source sensors until the MDC visits the sensors and downloads the information over a single-hop wireless transmission. 10
  11. 11. WSN network architecture and routing protocols• Multipath based networks 11
  12. 12. WSN network architecture and routing protocolsHeterogeneity based networks• A heterogeneous WSN consists of three types of nodes: sink node, high- end senor node (NH), and low-end senor node (NL). Each node has the same communication model and two types of sensor nodes have the same sensing model. The difference between NH and NL is that the different pre-defined communication and sensing range.• Heterogeneous wireless sensor network (heterogeneous WSN) consists of sensor nodes with different ability, such as different computing power , sensing range and communication range.In wireless sensor networks, cooperative routing protocols have found goodutility. The nodes in a group or cluster send data to cluster head or sink node,which aggregates data from many nodes and eliminates the redundant dataat this stage, which ultimately enhances the node and network lifetime.• Cluster based routing protocols work in two levels mostly, cluster heads are selected in first level and the second level is used for routing. composition of one round of the clustering process 12
  13. 13. WSN network architecture and routing protocols• Here the author summarized categories of routing protocols for various sensor networks. 13
  14. 14. Contents• Research Intention• Preparatory Concept• WSN network architecture and routing protocols• Data aggregation and fusion in WSN• Data aggregation protocols based on network architecture• Computational intelligence and data aggregation in sensor networks• Conclusion 14
  15. 15. Data aggregation and fusion in WSN• In Data aggregation/collection process data from sensors in an area is gathered (for performing fusion) to eliminate redundant data and provide only the useful fused /integrated information to the base station.• The sensor nodes send their data to the intermediate nodes for data aggregation which also normally includes the fusion process and then transmit the condensed data the base station or sink node.• The aim of data aggregation is to get the most relevant data from the data collected by the sensor nodes and make it available to the base station with minimum energy consumption and also with minimum delay.• Data aggregation mechanism is an important factor in the energy efficient sensor network along with network architecture and the underlying routing protocol. Data aggregation 15
  16. 16. Data aggregation and fusion in WSN• The Data aggregation techniques include data centric and address centric routing heuristics. The making of an optimal aggregation tree is NP-hard, but there exist some sub optimal solutions :• Center at Nearest Source Data Centric (CNSDC): In CNSDC, the node closest to the sink acts as the aggregator and the remaining nodes send their data to that node.• Shortest Path Tree Data Centric (SPTDC): A SPC is formed and merges the shortest paths from each source wherever these overlap in an opportunistic manner.• Greedy Incremental Tree Data Centric (GITDC): The algorithm starts with the path from sink to the nearest source, and sequentially adds the next nearest source to the existing tree.• Address Centric (AC): In address centric no data aggregation is performed and all the nodes communicate directly with the sink by using the shortest paths available.• Data aggregation has proven to save energy in many network applications. But data aggregation results in increased delay due to in network processing, so efficient routing algorithms may be designed to accommodate for this. Data aggregation 16
  17. 17. Data aggregation and fusion in WSN• In data fusion at a sensor node ,the data aggregated from multiple nodes is processed in such a way that the data generated after fusion has reduced the transmission overhead in the network.• Various Conventional techniques are used for data fusion include Kalman filter, Bayesian networks and Dempster-Shafer .• The data fusion process includes the collection of data at the fusion node from other nodes and fusing the sensed data with its own on the basis of pre decided criterion.• Data fusion criteria can be voting, probability-based Bayesian model and stack generalization and the voting scheme can be based on majority voting, complete agreement and weighted voting.• After fusion it transmits the data to another node or directly to the base station. The important considerations in data fusion include the reporting time, fusion criteria and the data fusion architecture. Data fusion 17
  18. 18. Data aggregation and fusion in WSNdata fusion architecture:-• In centralized architecture, the fusion process is performed at a central node. – Advantage: Erroneous report(s) can be easily detected. – Disadvantage: inflexible to sensor changes and the workload is concentrated at a single point.• In decentralized architecture, each node performs data fusion itself and no gathering of data at a fusion node is required. – Data fusion occurs locally at each node on the basis of local observations and the information obtained from neighboring nodes. – No central processor node. – Advantage: scalable and tolerant to the addition or loss of sensing nodes or dynamic changes in the network.• In hierarchical architecture, the nodes are divided into clusters or levels, and nodes send their data to the higher level nodes for fusion. – Nodes are partitioned into hierarchical levels. – The sensing nodes are at level 0 and the BS at the highest level. – Reports move from the lower levels to higher ones. – Advantage: Workload is balanced among nodes data fusion architecture 18
  19. 19. Contents• Research Intention• Preparatory Concept• WSN network architecture and routing protocols• Data aggregation and fusion in WSN• Data aggregation protocols based on network architecture• Computational intelligence and data aggregation in sensor networks• Conclusion 19
  20. 20. Data aggregation protocols based on network architecture• The architecture of the network influences the performance of the data aggregation technique being used. The network structures as already discussed can mainly be divided into Flat networks and hierarchical or cluster based networks. 20
  21. 21. Data aggregation protocols based on network architecture• The data aggregation techniques designed for flat networks include Push Diffusion, one phase Pull Diffusion and two phase Pull Diffusion. SPIN (Sensor Protocols for Information via Negotiation)protocol is the example of push diffusion, whereas directed diffusion is representative of two phase pull diffusion. These algorithms improved the performance of the network as compared to simple flooding in flat networks.• Hierarchical networks provide the advantages like scalability, energy efficiency over the flat networks. The hierarchical networks can be divided into different categories and data aggregation techniques have been proposed for each category.The cluster based hierarchical networking and data aggregation protocols for thiscategory need some unconventional solution from the fields like CI.LEACH :-LEACH stands for Low-Energy Adaptive Clustering Hierarchy – The Set-Up Phase • Where cluster-heads are chosen – The Steady-State • The cluster-head is maintained • When data is transmitted between nodes 21
  22. 22. Data aggregation protocols based on network architectureHEED :- Hybrid Energy Efficient Distributed Clustering• HEED was designed to select different cluster heads in a field according to the amount of energy that is distributed in relation to a neighboring node.• Four primary goals: – prolonging network life-time by distributing energy consumption – terminating the clustering process within a constant number of iterations/steps – minimizing control overhead – producing well-distributed cluster heads and compact clusters.CLUDDA :- Clustered Diffusion with Dynamic Data Aggregation• Generally two main phases involved in this kind of protocols are setup phase and steady state phase.• The setup phase involves the organization of the network into clusters and the selection of cluster heads.• The steady state phase involves data aggregation at the cluster heads and data transmission between nodes. 22
  23. 23. Contents• Research Intention• Preparatory Concept• WSN network architecture and routing protocols• Data aggregation and fusion in WSN• Data aggregation protocols based on network architecture• Computational intelligence and data aggregation in sensor networks• Conclusion 23
  24. 24. Computational intelligence and data aggregation in sensor networks• CI is defined as the computational models and tools of intelligence, that capable of inputting raw numerical sensory data directly, processing them by exploiting the representational parallelism and pipelining the problem, generating reliable and timely responses and withstanding high fault tolerance.• Here author proposed Data aggregation and fusion techniques based on computational intelligence for effective fusion of information gathered from different sensor nodes, the techniques that can adjust automatically.• many CI paradigms favor the problems of data aggregation and sensor fusion , those are evolutionary algorithms GA, fuzzy logic and NNs.• Efficient data aggregation routes have been achieved by GA in a mobile agent based WSN because of their inherent parallel nature and ability to deal with difficult real world problems like non-homogeneous, noisy, incomplete and/or obscured information.• Particle swarm optimization PSO can be a good alternate to GA because of PSO capability to converge quickly to the optimal solutions and to determine the optimal route paths. 24
  25. 25. Computational intelligence and data aggregation in sensor networks• For fusion process neural networks are well suited because neural networks can learn and dynamically adapt to the changing scenarios.• Reinforcement learning is fully distributed and it can adapt quickly to network topology change or any node failure. It has been used efficiently for finding the optimal path for data aggregation.• Fuzzy Logic based distributed approach using fuzzy numbers and weighted average operators to perform energy efficient flooding-based aggregation.• In wireless sensor networks many situations demand aggregating data at a central node e.g. monitoring events. For these situations, the centralized approaches like neural networks, GA or PSO can be used efficiently to know the features of the data. 25
  26. 26. Contents• Research Intention• Preparatory Concept• WSN network architecture and routing protocols• Data aggregation and fusion in WSN• Data aggregation protocols based on network architecture• Computational intelligence and data aggregation in sensor networks• Conclusion 26
  27. 27. Conclusion• Due to the several limitations of wireless sensor network, all CI techniques can not be applied in the field of data aggregation and data fusion in literature by researchers, as their characteristics do not suit data aggregation and fusion.• Data aggregation needs centralized approaches i.e. the data is gathered at a central node for performing processing and transmitting results, it results in increased communication overhead.• So distributed data aggregation technique under dynamic communication constraints may be suggested.• Future research is likely to focus on developing a well founded analytical approach to distributed multi-sensor data aggregation and fusion problems where there are time varying communication bandwidth constraints. 27

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