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Bichromatic Reverse Nearest Neighbours
- 1. Bichromatic Reverse Nearest Neighbours in Mobile P2P Networks Jessie Nghiem, Kiki Maulana Agustinus Borgy Waluyo, David Green, David Taniar
- 2. Inspiring example Earthquake and rescue teams 3/31/2013 2
- 3. Motivation Advances in mobile technology 3/31/2013 3
- 4. Motivation 1. Scalability Limitations of Centralized Systems 2. Bottleneck Moving objects Wide-range comm. 3. Low fault-tolerance Interest objects P2P comm. 3/31/2013 (a) Centralized Systems (b) P2P Systems 4
- 5. Ultimate Aim “… to harness collaborative power of peers for spatial query processing in Mobile Environment” 3/31/2013 5
- 6. Problem definition – Bichromatic Reverse Nearest Neighbour (BRNN) Query point Moving i0 objects Circle from the object of interest to its Bichromatic nearest moving object i1 Objects of interest io and i1 are the results of the RNN query from q 3/31/2013 6
- 7. Related work Propose: – Tao, Y., Papadias, D., Lian, X.: Reverse knn search in arbitrary dimensionality. • Limitations: P2P In: Proceedings of the Thirtieth – Centralized approach international conference on Very large data bases , VLDB '04. – Only deal with monochromatic RNNs H-(p0) Bichromatic Half-space pruning. Any point that lies in the shaded half- space H-(p0) is always closer to p0 than to q and cannot be the RNN for this reason. 3/31/2013 7
- 8. Definitions Negative half plane Positive half plane Query node Peer node Boundary line 3/31/2013 8
- 9. Definitions Object of interest o • Boundary region • If B is closed, B: boundary polygon. • The boundary polygon B is called a tight polygon iff any object of interest oi inside B regards q as the closest moving object. Boundary polygon B 3/31/2013 9
- 10. How to build a tight polygon The next processing peer is q4 outside C p4 C(q, qq0) TIGHT Boundary polygon Farthest vertex q0 P = {p0, p1, …, p4,,p5, p6, …} is a priority queue Reflection point of q thru v0 3/31/2013 10
- 11. Construct the polygon for filtering objects of interest 3/31/2013 11
- 12. Exhaustive Search vs Centralized Search Remarkably efficient in saving energy and time 3/31/2013 12
- 13. Only sends query to the peers that build B 3/31/2013 13
- 14. Optimized Search versa Exhaustive Search Approximate accuracy rate with less mean latency 3/31/2013 14
- 15. Simulation framework - Based on OMNet++ and MiXiM - Using network interface card which follows IEEE 802.15.4 standard for bluetooth networks 3/31/2013 15
- 16. Simulation framework Simulation model Parameters Value Playground 87.1km2 No. of MOs 7600 No. of IOs 550 Cache Size 50 Expected no. of 2 queries/MO Simulation time 30s 3/31/2013 16
- 17. Simulation Results – P2P Search versa Centralized Search 3/31/2013 17
- 18. Optimized Search versa Exhaustive Search 3/31/2013 18
- 19. Simulation Results – No. of Peers Pruned and Stop Hits 3/31/2013 Optimized Search Algorithm 19
- 20. Conclusion • P2P Search significantly save communication cost and 43% processing time compared to Centralized Search • Optimized Search reduces the number of queried peers and then response time while it maintains accuracy rate approximate to that of Exhaustive Search. • A practically feasible option for a large-scale and busy network 3/31/2013 20
- 22. 3/31/2013 22
- 23. Problem Statement • Let P and O be two sets of points in the same data space. • Given a point p є P, a BRNN query finds all the points o є O whose nearest neighbours in P are p, namely, there does not exist any other point p0 є P such that d(o, p0) < d(o, p). 3/31/2013 23
- 24. System Overview Beacon message Ack. message Query Peers Node Query message Reply message Communication between Query node and Peers Three phases: 1. Initialization and Peer Discovery 2. Constructing a Boundary Polygon and Sending Queries 3. Pruning Interest Objects 3/31/2013 24
- 25. Definitions • q, p • P ={p1,…. pH} is a priority queue of peers of q. |P| = H. • Boundary line (b1) • 3/31/2013 25
- 26. Lemma – How to build a tight polygon If ∃pi є priority queue P, such that dist(q; pi) ≥ dist(q; vj), then B is a tight polygon. Put another way, we do not need to consider remaining peers left in the queue P and stop creating the polygon. 3/31/2013 26
- 27. Simulation framework Connection Manager World • Based on OMNeT++ Moving object Object of interest 3/31/2013 27
Editor's Notes
- To illustrate what the research is doing, let’s imagine a scenario. There is an earthquake. people aredisconnected from the centralized BS. A number of rescuers spread and help injured immobile victims in theaffected area. The only way of communication is asking their peer rescuers to locate victims. It is called P2P communication. In order to reduce redundancy, optimize human resources and maximize the support, a rescuer would rather go for a victim who needs him most, or in another way, who considers him as the closest. This is an example of Bichromatic RNN queries in Mobile P2P Networks. Here the term “bichromatic” means query nodes and points of interest are of two different types. In this example rescuers are moving objects playing as query points or peers. Immobile victims are static points of interest.There are many other potential practical applications of our research. For in-stance, in everyday applications, police force can communicate with each otherto distribute their team members to locations that needs them most for ex-ample, car accident sites or traffic congestion intersections.
- Our research is motivated from two different aspects. First,the advances in mobile technology. Recently we have experienced the fast evolution in both mobile hardware and software. Your smart phone or tablet becomes more powerful than your parents' computer. Google has introduced its Nexus tablet featuring quad-core processor while LG and HTC have presented their quad-core phones running Ice Cream Sandwich (Google's Android 4.0) from the outset. It is the time to harness the computing power, intelligence and various functionalities of mobile devices
- Scalability, bottleneck and low fault-tolerance are critical issuesof those centralized approaches, especially in large-scale systems. In particular, those systems only contain a central point of failure, which is likely to becorrupt in several scenarios. For example, on a battle field or natural disaster,the headquarters is vulnerable to unavailability or traffic congestion
- Before going to the proposed algorithms, here are preliminary definitions q is the query nodep_1 is one of peers of qb1 is the boundary line or the perpendicular bisector between q and p1.b1 divides the whole plane into 2 half planes.H+(p1) is the positive half plane. Any object in this half plane is closer to q than p1. Similarly for the negative half plane H-(p1). Any object in this half plane is closer to p1 than q
- * If any of these issues caused a schedule delay or need to be discussed further, include details in next slide.
- * If any of these issues caused a schedule delay or need to be discussed further, include details in next slide.
- * If any of these issues caused a schedule delay or need to be discussed further, include details in next slide.
- An RNN query returns all objects which consider the query object as their nearest neighbour.Two types: Monochromatic RNN and Bichromatic RNN.
- * If any of these issues caused a schedule delay or need to be discussed further, include details in next slide.