Prestented by Zhi-Sheng, Lin Revenue Optimized IPTV Admission Control Using Empirical Effective Bandwidth Estimation IEEE TRANSACTIONS ON BROADCASTING, VOL. 54, NO. 3, SEPTEMBER 2008 Alan Davy, Member, IEEE, Dmitri Botvich, Member, IEEE, and Brendan Jennings, Member, IEEE Prestented by Zhi-Sheng, Lin

Outline What Problem with Streaming Video? Two Approaches to Solve This Problem Proposed Admission Control Framework Other Admission Control Simulation Model and Experimental Results Contribution of This Paper Some Drawback in This Paper

What Problems with Streaming Video? A problem with streaming video in congestion network Packet are dropped randomly. Packet loss & delay increased. Incur bad QoS. Two approaches to solve this problem. (next slide)

Some Approaches to Solve This Problem First Selectively adapt the quality of a subset of streams. (ex: adjust the transmission rate) Second Use admission control (AC) techniques. Seek to ensure that the adequate bandwidth is available within the network to sustain the high QoS targets for every flow that is accepted. AC can be divided into two types. (next slide)

Two Types of Admission Control First: Parameter based admission control. (PBAC) Pirori knowledge exists for the bandwidth requirements of each traffic source. (ex: peak rate, mean rate) Second: Measurement based admission control. Makes decision based on measurements taken in real time from the network. (ex: mean throughput and variance of traffic aggregates) Hybrid of both: Experience Based AC (EBAC). Measurement Based and a priori Traffic Descriptor AC (MTAC). PBAC 缺點: 那些資訊不會永遠被建立 MBAC缺點: 不正確的測量會導致不正確的有效頻寬估計

Proposed Admission Control Framework Scope: Unicast video-on-demand (VoD). QoS: Targets on packet delay. This framework is a hybrid AC: Analyze a trace relating to an aggregate of traffic flows collected over a set time interval. Descriptor: peak throughputs of the requesting flows.  priori information 透過量測某一段時間的effective bandwidth的值”R” R+近來的Traffic bandwidth peak throughput用來當作新的衡量標準 如果第二步驟的值可以滿足QoS目標，則接收該串流

Proposed admission control framework This framework consists of: A. Empirical Estimation of Effective Bandwidth B. Empirical Admission Control (EAC) Algorithm C. Revenue Maximizing Empirical Admission Control (RMEAC) Algorithm

A. Empirical Estimation of Effective Bandwidth Effective bandwidth can be defined for different types of QoS targets. (ex: delay, loss, or both) This paper addresses delay only. For example: delay target = (50ms, 0.001), that is only 0.1% of traffic is allowed to be delayed by more than 50ms.

A. Empirical Estimation of Effective Bandwidth 2019/4/29 A. Empirical Estimation of Effective Bandwidth Delay targets = {delaymax, pdelay} For instance, {50ms, 0.01} // Current queue volume // 封包可以處理完的時間點 To estimate the effective bandwidth of a particular traffic source on the network, we take a recorded packet trace of that source. Initialization // 累計的處理封包量 // 累計的延遲量 // 針對R速度與delaymax // 計算最大的queue容量

A. Empirical Estimation of Effective Bandwidth Processing the packets in the trace to calculate the delay that over the maximum delay.

A. Empirical Estimation of Effective Bandwidth 2019/4/29 A. Empirical Estimation of Effective Bandwidth // 允許的誤差值 The effective bandwidth lies between these two values. 在reference [23]有提到為什麼effective bandwidth要介於mean rate跟peak rate之間

A. Empirical Estimation of Effective Bandwidth 2019/4/29 A. Empirical Estimation of Effective Bandwidth Wow!! Binary search here. // 找出來的queue service rate // 用來當effective bandwidth.

A. Empirical Estimation of Effective Bandwidth Example of function calcViolations(delaymax, R, TM)

B. Empirical Admission Control (EAC) Algorithm

B. Empirical Admission Control (EAC) Algorithm Empirical concept Descriptor

C. Revenue Maximizing Empirical Admission Control (RMEAC) Algorithm The objective is to use historical information about content item request arrivals, together with associated cost and resource requirements, to maximize expected revenue.

Item i 產生的收入 Item i 的持續時間 在 t-t’ 到 t 這段時間 要求item i 的次數 在 t 到 t+t’ 這段時間 marginal utility Marginal臨界的

C. Revenue Maximizing Empirical Admission Control (RMEAC) Algorithm Marginal utility The probability of an arrival of an additional request for the item during the interval.

C. Revenue Maximizing Empirical Admission Control (RMEAC) Algorithm

C. Revenue Maximizing Empirical Admission Control (RMEAC) Algorithm

C. Revenue Maximizing Empirical Admission Control (RMEAC) Algorithm

C. Revenue Maximizing Empirical Admission Control (RMEAC) Algorithm

C. Revenue Maximizing Empirical Admission Control (RMEAC) Algorithm

Other Admission Control Experience Based AC (EBAC). Measurement Based and a priori Traffic Descriptor AC (MTAC). Parameter Based AC (PBAC).

Simulation Model Service provider When bandwidth used up to 90% of the capacity, start admission control. 2019/4/29

Simulation Model (1) User Profile 2019/4/29 Simulation Model (1) User Profile Use a standard Poisson arrival process to generate arrivals with the expected mean arrival rate calculated from the corresponding hour period within Fig.2. 2019/4/29

Simulation Model (2) Service Popularity and the Pareto Distribution 2019/4/29 Simulation Model (2) Service Popularity and the Pareto Distribution Most popular content will contribute to a high percentage of the overall requests. (80:20 rule) (3) Traffic Models and Characteristics Video frame trace with MPEG-4 and H.263 format. Simplifying assumption: customer will view the item for complete duration. 80:20 rule. 2019/4/29

Simulation Model i: item rank (class1-3) req.arr.rate: request arrival rate R(i): revenue, cost p(i): peak rate Ti: duration 2019/4/29

Simulation Model (4) Pricing Model (5) QoS Violation Measurement TABLE IV  class 1 to class 3, the popular content is more expensive. (5) QoS Violation Measurement Measure QoS violations within the network by collecting a packet trace at a point following admission control and processing it through our FIFO queue algorithm. Simulation Result (see next Slide) 2019/4/29

Reflection of statistical multiplexing effect 2019/4/29 Reflection of statistical multiplexing effect EAC More accurately predict the level of bandwidth necessary to ensure QoS targets on traffic are maintained. As traffic is multiplexed, the required effective bandwidth for the aggregated traffic is reduced in proportion to the overall mean throughput of service flows admitted. Effective bandwidth coefficient = prediction of bandwidth required by each AC algorithm to perform AC 除於 current mean throughput Effective bandwidth coefficient = prediction of bandwidth required by each AC algorithm to perform AC / current mean throughput 2019/4/29

Utilization QoS target on packet delay of (0.02s, 0.0001) MTAC EAC 2019/4/29

QoS violation QoS target on packet delay of (0.02s, 0.0001) 2019/4/29

Table: comparison of different AC algorithm in this scenario 2019/4/29 Table: comparison of different AC algorithm in this scenario QoS target on packet delay of (0.02s, 0.0001) AC algorithm Utilization of bandwidth OoS violations else EAC (this paper) ~50 Mbps None An appropriate control of bandwidth with respect to QoS targets. PBAC ~25 Mbps Under-utilization of available resources. MTAC ~75 Mbps High Under-estimation of required resources. EBAC ~85 Mbps A little in this case Over-estimates the maximum link utilization. 2019/4/29

With relaxed QoS targets -- utilization QoS target on packet delay of (0.04s, 0.0001) 2019/4/29

With relaxed QoS targets – Qos violation QoS target on packet delay of (0.04s, 0.0001) 2019/4/29

Analysis of RMEAC Versus EAC – class 1 item 2019/4/29 Analysis of RMEAC Versus EAC – class 1 item RMEAC: prioritize higher value services. EAC: First-come-first-served 2019/4/29

Analysis of RMEAC Versus EAC – class 2 item 2019/4/29

Analysis of RMEAC Versus EAC – class 3 item 2019/4/29

Contribution of This Paper reaching the appropriate trade-off between ensuring QoS targets are met and not over-allocating bandwidth. RMEAC can outperform EAC in terms of maximizing the revenue generated for the service provider by admitted traffic flows.

Some Drawback in This Paper Mentioned in this paper Central vs Distributed management Some simplifying assumption Ex: admitted flows are not interrupted by the user.

Some Drawback in This Paper 要列表格來說參數代表意義，就請詳細列出來，而不是有些在文章內提及 演算一有一列縮排錯誤 演算法三第一步驟最後兩列最好也縮排一下，不然就重複計算了 在606頁右下，Pricing Model提到Class 1是最多要求的，但從表二來看卻不然 圖三有錯誤EEAC應為EAC

~Thanks for your listening~