A Utility-based Mechanism for Broadcast Recipient Maximization in WiMAX Multi-level Relay Networks Cheng-Hsien Lin, Jeng-Farn Lee, Jia-Hui Wan Department of Computer Science and Information Engineering, National Chung Cheng University, Taiwan IEEE Transactions on Vehicular Technology (IEEE TVT 2012)

Outline  Introduction  Goal  Network Model and Assumption  Problem specification  Multi-Level Utility-based Resource Allocation (ML-URA)  Simulations  Conclusions 2

Introduction  The emergence of IEEE WiMAX and advances in video coding technologies have made real-time applications possible.  The granted applications (e.g., real-time IPTV Broadcast)  Allocated limited time-slots (Resource Budget). 3

Problem  This paper studies the resource allocation problem  Broadcast receipt maximization in IEEE j  IEEE j  Multihop Relay Base Station(MR-BS)  multiple Relay Stations(RSs)  Mobile Stations(MSs)  Broadcast data is sent by the MR-BS to a set of receivers  How to allocate the given resource budget to maximize the number of MSs is a challenging issue. 4

Problem  The broadcast receipt maximization problem 5

Problem  The broadcast receipt maximization problem 6

Problem  The broadcast receipt maximization problem 7

Problem  The broadcast receipt maximization problem 8

Related works  Existing researches  heuristic resource allocation strategies  single-level relay networks (two-hop relay networks)  This paper models the resource allocation problem in IEEE j WiMAX multi-level relay networks (multi-hop)  Multi-Level Broadcast Receipt Maximization (ML-BRM) problem 9

Goal 10  To propose multi-level resource allocation mechanism  Consider the multi-level relay paths and the required resource  Maximize resource utilization in WiMAX multi-level relay networks

Network Model and Assumption  In a WiMAX relay network,  one MR-BS  Y RSs  N MSs that subscribe to a certain real-time program  This paper assumes that the real-time program, whose streaming data size is M  Resource budget: r budget  total time slots in a TDD super frame RS 0 Each RS y (1 ≤ y ≤ Y) is denoted by RS y Each MS n (1 ≤ n ≤ N) is denoted by MS n 11

Network Model and Assumption  The number of time slots required to transmit a broadcast stream varies  MSs and RSs have different channel conditions  MSs and RSs have different modulation schemes  the transmission rates required for RSs to successfully send data also vary 12

Network Model and Assumption  The transmission rate b x,y between sender x and receiver y  based on one of the channel conditions, such as the SNR value  sender x: MR-BS or RS  receiver y: RS or MS  The resource required by the receiver y: M/b x,y 13

Network Model and Assumption  RA x : a node x with the allocated resource RA x  all nodes whose required resource is not larger than RA x can receive the downlink data successfully through one downlink transmission from node x. x x MS RA x 14

Network Model and Assumption  For all RSs, the channel conditions are represented by where records the resource required by RS y to receive streaming data from other RSs.  RRes y,y = 0: RS y doesn’t demand any resource from itself. RS2 RS0 RS4RS8RS5RS3RS1RS6RS

Network Model and Assumption  Similarly, the matrix portrays the resource requirement of all MSs, where records the resource that MS n requires to receive data from all RSs. MS1MS2 RS2 RS0 RS4RS8RS5RS3RS1RS6RS7 16

Network Model and Assumption  Finally, the resource allocation vector is denoted by RA = [RA 0, RA 1, RA 2, …, RA Y ], where RA y represents the amount of the resource allocated to RS y. MS1MS2 RS2 RS0 RS4RS8RS5RS3RS1RS6RS7 17

Network Model and Assumption  U(  ): whether the MS n can receive data from RS y successfully. 18 MS1 RS0 RS1 RA 1 = 5 MRes 1,1 = 3 MS2 MRes 2,1 = 7 U(RA 1 -MRes 1,1 ) = U(5-3) = 1  U(RA 1 -MRes 2,1 ) = U(5-7) = 0

Network Model and Assumption  D(  ): whether RS y is eligible to receive real-time streaming data from the MR-BS when the current resource allocation RA is given.  D 0 (RA) = 1: MR-BS is the source node of the real-time stream. 19 RS0 RS1 RA 1 = 5 RRes 2,1 = 3 RRes 3,1 = 7 RS3RS2 D 2 (RA) = D 2 (5-3) = 1  D 3 (RA) = D 3 (5-7) = 0

Problem specification  We now define the Multi-Level Broadcast Recipient Maximization (ML-BRM) problem.  resource budget (r budget )  channel conditions of the wireless relay network (R MS and R RS )  ML-BRM searches for an allocation RA vector that will maximize the number of MSs receiving the real-time program. The ML-BRM problem is NP-complete 20

ML-URA  Multi-Level Utility-based Resource Allocation  Definition of Utility  u i,y : the number of additional MSs divided by the extra resource that the network must allocate to the RSs on the relay path 21

ML-URA  Construct single-source shortest path tree that is rooted at the MR-BS and connects all RSs. (SP y )  ѱ (SP y ) counts the number of RSs on SP y  Γ(SP y, k) obtains the ID of the kth RS on SP y, 1 ≤ k ≤ ѱ (SP y ) RS2 MR-BS RS4RS8RS5RS3RS1RS6RS7 SP 1 SP 6 ѱ (SP 6 ) = 2 Γ(SP 6, 1) = 1 Γ(SP 6, 2) = 6 22

ML-URA  To derive the utility of a relay path u i,y  count the number of additional MSs  calculate the amount of extra resource required 23 RS0 RS k RS k+1 MS j check if MS j can be served by SP y ……... RS y ……... Because of the broadcast nature of the wireless medium, MS j can receive data of the real-time program

ML-URA  To derive the utility of a relay path u i,y  count the number of additional MSs  calculate the amount of extra resource required 24 RS y is allocated MRes i,y to serve MS i check if MS j can be served by RS y RS y MS j MS i Because of the broadcast nature of the wireless medium, MS j can receive data of the real-time program

ML-URA  the union operation 25 the additional number of MSs that can be served whether MS j has been served in previous rounds of the resource allocation process

ML-URA  To derive the utility of a relay path u i,y  count the number of additional MSs  calculate the amount of extra resource required 26 RS0 RS k RS k+1 MS i ……... RS y ……...

ML-URA  To derive the utility of a relay path u i,y  count the number of additional MSs  calculate the amount of extra resource required 27 RS k MS i Rs k+1

ML-URA  The expression of the utility of a relay path u i,y is defined as follows: 28

ML-URA  The ML-URA Mechanism  Greedy procedure  Find-Most-MS-Path procedure 29 (u i,y ) (number of MSs)

ML-URA _Greedy procedure 30 Greedy procedure stop conditions exists: (i) the entire resource budget has been allocated (ii) all MSs have been served.

ML-URA _Greedy procedure  Resource-Recycle procedure 31

ML-URA _Greedy procedure  Two distinct paths that have the same utility value 32 5/52/2

Find-Most-MS-Path procedure ML-URA _ Find-Most-MS-Path procedure 33

ML-URA _ Find-Most-MS-Path procedure 34

Simulations 35

Simulations 36 => computes the optimal solution in a brute-force manner

Simulations 37

Simulations 38

Conclusions  The proposed ML-URA mechanism improve  Resource utilization  Performance 39