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Explore the integration of cellular and ad-hoc networks to improve network capacity, throughput, delay, and power consumption. Comparison of models, iCAR system, and simulations analyzed for the hybrid approach.
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Hybrid Networks Presented By Kevin Hofstra CS ‘03
Outline • Two models of wireless communications • Comparison of the two models • Hybrid networks • Using ad-hoc to help cellular • iCAR • Current work
Two Models of Wireless Communications • Cellular infrastructure • Ad-hoc peer-to-peer infrastructure
Cellular Infrastructure • Base station on wired network
Ad-Hoc infrastructure • Peer-to-peer network • No underlying network needed
Outline • Two models of wireless communications • Comparison of the two models • Based on HS01 • Hybrid networks • Using ad-hoc to help cellular • iCAR • Current work
Simulation Environment • ns-2 network simulator • Physical layer • Single channel communication (2 Mbps) • Free space propagation and two-ray ground reflection channel models • Medium access layer • Cellular model: IEEE 802.11 PCF (round-robin) • Ad-hoc model: IEEE 802.11 DCF / IFS / ILS • Routing layer • Cellular model: no routing required • Ad-hoc model: DSR (dynamic source routing)
Simulation Environment • Topology • 1500m by 1500m grid with randomly distributed nodes (50 –400 nodes) • Transmission range • Cellular model: 750 • Ad-hoc model: variable (MIN to MAX) • Mobility • Waypoint movement model • Traffic generation • Every node acts as a CBR source with randomly chosen destination (light to heavy load) • Use TCP to transport CBR traffic
Metrics • Network capacity • End-to-end throughput • End-to-end delay • Power consumption • Fairness • Impact of mobility
Network Capacity • Network capacity • Proportional to the number of simultaneous transmissions (spatial reuse) and channel data rate • Destination is one-hop away from the source • Upper bound for instantaneous traffic • Unfair MAC vs. fair MAC • Network capacity ~ O(Node number) = O(n)
Throughput Degradation • End-to-end throughput degradation • Network failures (due to mobility) reduce network throughput • Route failures cause packet loss and stall TCP transmission • Route recovery process consumes network resource
Outline • Two models of wireless communications • Comparison of the two models • Hybrid networks • Using ad-hoc to help cellular networks • iCAR • Current work
Relieving congestion in Cellular networks • Balance the traffic in a network of multiple base stations • Relay traffic from Congested cells to neighbors with free bandwidth • PARCelS: Pervasive Ad-hoc Relaying for Cellular Systems by Jie Zhou and Richard Yang • iCAR
iCAR : an Integrated Cellular and Ad-hoc Relaying System * Hongyi Wu Advisor: Dr. Chunming Qiao LANDER, SUNY at Buffalo This project is supported by NSF under the contract ANIR-ITR 0082916 and Nokia.
Outline • Motivations • Introduction of iCAR • ARS Placement • Seed ARS • Quality of Coverage • iCAR Performance • Simulations • Signaling Protocols • Future Work and Conclusion
What is a cellular system? • The problem of scarce frequency resource • Based on subdivision of geographical area • One Base Transceiver Station (BTS) in each cell. • Frequency is reused in cells far away.
A MH can only access the channels in one cell (except soft-handoff). Unbalanced traffic among cells Variable locations of the Hot Spots (congested cells) Tremendous growth of wireless data/voice traffic Limited capacity Problems in Cellular Systems
Objectives of Our Work • Balance traffic among cells • Decrease call blocking and dropping probability • Increase system’s capacity cost-effectively • Support heterogeneous networks • Reduce mobile host’s (MH) transmission power and/or increase transmission rate
Outline • Motivations • Introduction of iCAR • iCAR Placement • Seed ARS • Quality of Coverage • iCAR Performance • Simulations • Signaling Protocols • Future Work and Conclusion
Basic Idea : Integration of Cellular and Ad-hoc Relaying Technologies • ARS : Ad-hoc Relaying Stations • Each ARS and MH has two interfaces (celluar and relay) ARS MH
One example of relaying • MH X moving into congested Cell B is relayed to Cell A x A B A B x (a) (b)
An ARS differs from a BTS and a MH • Compared to BTS • Mobility • Air interface • Compared to MH • Mobility • Security,authentication,privacy • Billing
Basic Operations • Primary Relay : a strategy that establishes a relaying route between a MH (in congested cell) to a nearby non-congested cell. • Failed Hand-off • Blocked new call • MH switches over from C-interface to R-interface A B x
Basic Operations (Cont’d) • Secondary Relay • Primary relay failed • Not covered by ARS • Reachable BTS is congested too • Free the channel of an active call which can be relayed to a neighbor cell x A B y (a) x A B y (b)
Basic Operations (Cont’d) • Cascaded Relay • Cascade the above relays more multiple times if they are failed. x x A B A B y y z z C C
CI and NCI • Congestion-Induced (CI) Relaying • Reduce call blocking or dropping probability when congestion occures. • Noncongestion-Induced (NCI) Relaying • Pro-actively balance load • Shadowing Area • Uncovered Area • Transmission Power
Outline • Motivations • Introduction of iCAR • ARS Placement • Seed ARS • Quality of Coverage • iCAR Performance • Simulations • Signaling Protocols • Future Work and Conclusion
Full Coverage • The maximum number of relay stations needed so as to ensure that a relaying route can be established between any BTS and an MH located any where in the cell 2 Km 1.5 Km 1 Km 200m 50 200 114 18 350m 66 38 500m 8 18 32
Seed Growing Approach • With fewer ARS’s, relaying can still be effective. Some can be seeds (placed at each pair of shared edges), and others can grow from them (placed nearby).
Number of Seed ARSs • For a fix coverage area, the system with fewer UN-SHARED edges needs more seed ARSs. • The max number is obtained by considering a circle area and count the number of shared edges. Proposition: For a n-cell system, the maximum number of seed ARS’s is
Quality of Coverage • The quality of ARS coverage (Q) is defined to be the relay-able traffic in an iCAR system. • The Q value depends on the traffic intensity, the cell size, the ARS size, the system topology, etc. • The higher the Q value, the better the ARS placement • The Q value is not always proportional to the ARS coverage.
Seed ARS’s Placement B • Two approaches to place the seed ARS • Edge (ARS No.1) • S: ARS ceverage; • TA, TB: Traffic intensity of cell A and B. • bA,bB: Blocking probability of cell A and B. B B A 2 2' 1 B B 1' B Seed ARS’s 3 3' … Half of S covers cell A, but only unblocked part (1-bB) of them is relay-able
Seed ARS’s Placement B • Vertex (ARS No.1') B B A 2 2' 1 B B 1' B Two third of S covers cell B. .. One third of S covers cell A. Note that, the Blocking probability is bB2 because the call may Be relayed to two cells. Seed ARS’s 3 3'
Seed ARS’s: Edge v.s. Vertex • Preliminary results • Case1 : when TB<TA<50 Erlangs, Qvertex<QEdger. • Case2 : when TA, TB>50 Erlangs or TA<TB, QVertex>QEdge. • Case2 is out of normal operation range • Rule of Thumb 1 • Place the seed ARS's at edges of a hot spot cell.
Seed ARS v.s. Grown ARS • Preliminary Results • Case1 : seed (ARS 2). Assuming edge placement of seed) • Case2 : grow (ARS 2’). The QoC value of the grown ARS is about 0.61•S •TA•(1-bB). • Rule of Thumb 2 • Try to place an ARS as a seed if it is possible.
Growing Direction • When there are already sufficient seed ARS’s, • Additional ARS's can grow • toward inside of a hot cell A (ARS No.3) • toward outside of cell A (ARS No.3') • Rule of Thumb 3 • Place an ARS in the cell with a higher traffic intensity.
Outline • Motivations • Introduction of iCAR • ARS Placement • Seed ARS • Quality of Coverage • iCAR Performance • Simulations • Signaling Protocols • Future Work and Conclusion