AMAC Adaptive Medium Access Control for Next Generation

A-MAC: Adaptive Medium Access Control for Next Generation Wireless Terminals Mehmet C. Vuran, Member, IEEE, and Ian F. Akyildiz, Fellow, IEEE School of Electrical and Computer Engineering, Georgia Institute of Technology IEEE/ACM TRANSACTIONS ON NETWORKING, VOL. 15, NO. 3, JUNE 2007 R 96725018 陳品宏 R 96725044 曾有德

Outline I. III. IV. V. VII. Introduction Related Work The Virtual Cube Concept Network Modeling A-MAC: Adaptive Medium Access Control Performance Evaluation Conclusion 2

I. Introduction 3

Next Generation Wireless Networks ¡ Next Generation (NG) wireless networks are envisioned to provide high bandwidth to mobile users via bandwidth aggregation over heterogeneous wireless architectures ¡ The various types of MAC protocols: TDMA, CDMA, WCDMA and CSMA/CA ¡ Qo. S classes: Conversational, streaming, interactive and background Fig. 1. Next generation wireless networks. 4

Challenges ¡ Heterogeneity in Access Schemes: Different access schemes in different wireless networks ¡ Heterogeneity in Resource Allocation: No unified metric for comparison of the allocated resources ¡ Heterogeneity in Qo. S Requirements: The MAC layer must efficiently evaluate the available resources in different networks to satisfy the Qo. S requirements 5

The Structure and The Components of A -MAC ¡ Two-layer Adaptive Medium Access Control (A-MAC) ¡ Access sub-layer: Specialized for accessing the network ¡ Master sub-layer: Perform decision and scheduling requests for the most efficient network ¡ A novel Virtual Cube concept is used to model the networks Fig. 2. Main Components of A-MAC. 6

Main Object ¡ Incompatibility among medium access and resource allocation techniques are melted into a unified medium access control framework, providing self-contained decision flexibility as well as capability to access various networks. 7

II. Related Works 8

Related Works ¡ An Ad-hoc CEllular NETwork (ACENET) ¡ TCDMA protocol ¡ Hybrid TD/CDMA systems ¡ A multiple access protocol of cellular Internet and satellite-based networks ¡ The proposed methods requires either a modification in the existing infrastructure and base stations or a completely new architecture ¡ Integration problems: Implementation costs, scalability and backward compatibility 9

Assumption ¡ NG wireless terminals are capable of receiving signals from multiple network access points and transmitting signals to different access schemes simultaneously. 10

III. The Virtual Cube Concept A. Resource-Space B. Virtual Cube Structure 11

Resource-Space ¡ Time Dimension: The time required to transfer information ¡ Rate Dimension: The data rate of the network ¡ Power Dimension: The energy consumed for transmitting information through the network 12

Virtual Cube Structure ¡ Three parameters: Cube Capacity (M bits/cube) Cube Power (P Watts/cube) Cube Duration (T sec/cube) ¡ Two types of virtual cubes are VPC M used in the A-MAC: VIC Virtual Information Cube (VIC): The information sent through the network Virtual Power Cube (VPC): The additional power needed to transmit M bits of information Fig. 3. Virtual cube model. 13

IV. Network Modeling A. TDMA Modeling B. CDMA Modeling C. CSMA Modeling D. Multi-Rate Networks 14

TDMA Modeling ¡ A TDMA slot is characterized by slot duration and transmission rate ¡ Each interface is characterized by an average energy per bit ¡ The number of virtual cubes that can be filled in three dimensions of a resource bin: (1) Fig. 4. (a) TDMA and CDMA modeling. 15

CDMA Modeling ¡ Direct Sequence-CDMA (DS-CDMA) each bit of duration is coded into a pseudo-noise code of chips of duration the spreading gain the transmitted energy per bit is the bandwidth , is the data rate and is the transmitted signal power ¡ TDD CDMA the time is divided into radio frames, slots and sub-frames is determined by the length of the allocated slot ¡ FDD CDMA is determined by the duration of the connection 16

CSMA Modeling ¡ IEEE 802. 11 ¡ It is impossible to deterministically calculate the transmission time in CSMA based systems ¡ Using the last transmission information to model the resource bin Fig. 4. (b) CSMA Modeling. 17

Multi-Rate Networks ¡ Multi-code CDMA, e. g. , IS-95 -B and cdma 2000 ¡ The number of virtual cubes in the rate dimension, , of the CDMA frame model increases with the data rate ¡ The power level, , for a CDMA signal with a spreading gain , where is the power level of the fundamental spreading gain and is the fundamental spreading gain Fig. 4. (c) Multi-code CDMA modeling. 18

Multi-Rate Networks (cont. ) ¡ Multi-channel communication, e. g. , cellular networks and IEEE 802. 11 standard ¡ The number of virtual cubes in the rate dimension, , depends on many channel and transceiver dependent parameters such as the channel bandwidth, modulation and channel coding schemes Fig. 4. (c) Multi-channel modeling. 19

V. A-MAC: Adaptive Medium Access Control A. Decision B. Scheduling C. Adaptive Network Interfaces (ANIs) 20

The Structure and The Components of A-MAC Fig. 2. Main Components of A-MAC. 21

Decision ¡ A-MAC performs decision in each decision interval ¡ For a specific traffic flow , the decision block chooses the interface such that the utility function (2) ¡ Aims to find the interface with maximum throughput capability for the minimum transmission power 22

Decision (cont. ) ¡ Constraints: (3) (4) is the bandwidth share of the traffic in interface ¡ is the maximum power dissipation allowed for the decision interval ¡ is the minimum required bandwidth in terms of VICs for the traffic type in order to guarantee its Qo. S requirements ¡ is the set of active interfaces that are chosen by the decision 23 block ¡

Decision (cont. ) 1) 2) Single Type Traffic—Single Interface (STSI) Single Type Traffic—Multiple Interfaces (STMI) If the (3) and (4) are met by one or more interfaces, the one that maximizes (2) is chosen else… ¡ the interfaces are sorted in a decreasing order of their utility functions ¡ the constraint (4) becomes (5) ¡ A weight is associated with interface (6) 24

Decision (cont. ) 3) Multiple Type Traffic—Single Interface (MTSI) checks if the decision constraints hold for each traffic type each eligible traffic type is assigned a bandwidth share such that checks if each flow satisfies (3) and (4) ¡ the scheduler is informed of the bandwidth shares and MAC frame size of the interfaces ¡ or the traffic type with the lowest priority is rejected and the bandwidth shares are updated 4) Multiple Type Traffic—Multiple Interfaces (MTMI) 25

Scheduling ¡ In designing a scheduler, the requirements are considered: Qo. S Guarantee Channel Dependent Scheduling Dynamic Behavior Implementation Complexity ¡ Bin Sort Fair Queuing (BSFQ) scheduler Frame-based method uses virtual time stamps to determine the scheduling order Built-in buffer management component 26

Packets from the current bin are transmitted, and updates The current bin has the τ( t ) = t 2 label BSFQ method virtual system clock Δ Each bin is implicitly labeled outputtime buffer is and with. The a virtual interval organized into bins Δ each interval has. Nlength [ , + ) [ , The i-th bin has the label + ) Fig. 1. Bin Sort Fair Queuing. 27

BSFQ method (cont. ) ¡ The output buffer is organized into N bins ¡ Each bin is implicitly labeled with a virtual time interval and each interval has length Δ ¡ The current bin has the label The ith bin has the label Only packets from the current bin are transmitted Bin list is cyclic-list ¡ The output link rate may change during the connection time due to wireless channel conditions ¡ In order to prevent fluctuations in the bandwidth share of flows, the scheduler updates each bandwidth share in each decision interval 28

BSFQ method (cont. ) ¡ The jth packet of flow f is assigned with the virtual time stamp is the arrival time of packet is the length of is the reserved data rate of f 29

BSFQ method (cont. ) ¡ The index of the bin used to store packet is equal to: If = 0 then is stored in the current bin. If < N then is stored in the -th bin following the current bin. If > N then the packet is discarded. 30

Adaptive Network Interfaces (ANIs) 1) Network Structure Awareness 2) Network Modeling 3) gathering information about the underlying network structures achieved in different wireless systems, i. e. , GSM, UMTS, cdma 2000, and WLAN ANIs model or update the network MAC structure (resource bin) and inform the master sub-layer Access and Communication An ANI performs access to the network if it is selected for a transmission by the master sub-layer The communication with the AP is performed according to the network specific procedures 31

VI. Performance Evaluation A. Traffic Models B. Network Models C. Simulation Results 32

Traffic Models Exponential distribution and Modeling based on a threestatistically independent step Morkov model. distribution Exponential The stations generate IP packets with length of 260 bits in every 20 seconds Exponential distribution The bit rate in each state is determined independently. Exponential using a truncated exponential distribution Modeling with a multi-state model. distribution The length of each packet is geometrically distributed and independent of each other 33

Network Models 34

Simulation Results ¡ In a 200 m × 200 m grid, nodes are placed with uniform ¡ ¡ distribution Adaptive Node refer to the node equipped with A-MAC Analyze the performance of A-MAC with different number of nodes and different percentage of traffic distribution in the heterogeneous network structure Each simulation lasts 230 s and the results are average of 5 trials for each 5 random topologies Two sets of simulations: Fixed Topology and Dynamic Topology 35

Fixed Topology ¡ All nodes are stationary ¡ The adaptive node is assumed to be in the coverage area of three of the network structures ¡ The traffic type distribution (Voice, ABR, CBR, VBR) is chosen as (65%, 10%, 10%) ¡ , and denote the percentage of nodes in TDMA, CDMA and WLAN networks 36

Fixed Topology (cont. ) Fig. 5. Average throughput of voice traffic with (b) (50%, 30%, 20%). = (a) (10%, 80%), 37

Fixed Topology (cont. ) Fig. 5. Average throughput of CBR traffic with (d) (50%, 30%, 20%). = (c) (10%, 80%), 38

Fixed Topology (cont. ) Fig. 6. Average throughput of best-effort traffic with (b) (50%, 30%, 20%). = (a) (10%, 80%), 39

Dynamic Topology ¡ 100 mobile nodes ¡ The adaptive node roams through TDMA to the CDMA network, passing through the coverage area of WLAN APs ¡ The simulation lasts 230 s ¡ Averaging the throughput for intervals of 5 Fig. 7. Sample topology used in the mobility simulations. ●: TDMA BS; ◆: CDMA BS; ■: WLAN AP. 40

Dynamic Topology (cont. ) Fig. 8. (a) Throughput of voice traffic in dynamic topology. 41

Dynamic Topology (cont. ) Fig. 8. (b) Throughput of CBR traffic in dynamic topology. 42

Dynamic Topology (cont. ) Fig. 8. (c) Throughput of VBR traffic in dynamic topology. 43

Dynamic Topology (cont. ) Fig. 8. (d) Throughput of ABR traffic in dynamic topology. 44

VII. Conclusion 45

Conclusion ¡ Adaptive medium access control (A-MAC) for NG wireless terminals Novel virtual cube model Network modeling Qo. S-based decision Qo. S-based scheduling ¡ The first effort on designing a MAC protocol that achieves adaptation to multiple network structures with Qo. S aware procedures ¡ Doesn’t require any modifications to the existing network structures ¡ A cost function can be incorporated into the network modeling framework as a fourth dimension in the virtual cube concept such that the decision is performed accordingly 46

Thanks for your listening.