Deadline-based Resource Management for Information- Centric Networks Somaya Arianfar, Pasi Sarolahti, Jörg Ott Aalto University, Department of Communications and Networking ACM SIGCOMM workshop on ICN, 2013 Siran Zhang Park Lab, Waseda University 1

OUTLINE Introduction Network model Packets with lifetimes Queues with lifetimes Network resource management Evaluation Conclusion 2

Introduction (1) RTT (round-trip time) measurement plays an important role in IP network. Retransmission timers are typically set based on RTT. RTT is a factor that affects the rate of congestion control adjustments in protocols such as TCP. Assumption: end hosts remain the same. In ICN, RTT measurement becomes a nearly useless concept. Even RTT distribution of past data is known, it may not match the upcoming data. Buffering (caching) does not make RTT estimation any easier. 3

Introduction (2) So we propose an alternative way to approach data retransmission and resource management: Each network packet is supplied with a lifetime that tells how long it lives in the network before being dropped. From lifetime, receivers knows when to re-request data; Routers can use the lifetime as a part of queue management policy. In interest packets, lifetime is used to predictively discard them. 4

Network model: packets with lifetimes The sender of packets initializes the packet lifetime (in their headers), based on the application requirements of the networking. In the proposal, we will use “wallclock time” (not hop count) to indicate lifetime. Synchronized clocks should be made: making adjustments between different nodes. 5

Network model: queues with lifetimes Scheduling purposes queues are inevitable in any network, including ICN. Here we use the communication model of CCN. The router queue is divided into N subqueues. “T” indicates the starting time of the first queue. At any moment, current time is between T and T+K. The first subqueue contains packets with deadlines between T and T+K, and so on. When time reaches T+K, the first queue is discarded. For each node, N and K is independent of other nodes 6

Network model: network resource management (1) Before acting on a data request (interest), the router checks the current load on the return path, and calculates whether it is possible to deliver the response with the assigned lifetime. If it is not possible, the data request is dropped immediately. Assumption (eg. In CCN): when data packet is sent in response to the interest, it inherits the lifetime from the interest packet. 7

Network model: network resource management (2) When an interest packet arrives at the router, it evaluates the queue stack both on: the next hop interface, to see whether the interest packet can be forwarded in time; The previous hop interface, to estimate whether the returning data can be delivered in time. If either of the tests indicate that packet cannot be delivered in time, the interest packet will be discarded. If the data is in the content store, the data is just queued, based on deadline received on arriving interest. The router calculates the number of interests in the queue before the current interest, and estimated the queue delay based on outgoing link bandwidth. The router makes an pre-allocation for the expected upcoming data packets. 8

Network model: network resource management (3) Interest packet QiQi QdQd qiqi qdqd JiJi JdJd Data expected to arrive 9 threshold: calculated maximum amount of data that can be delivered to the link before the deadline S: the amount of data currently sub- queues that will be sent before the newly arrived interest packet (Si), or the data packet expected to arrive (Sd).

Network model: network resource management (4) 10 When the data corresponding to the interest arrives, it is placed on q d. And the value of PreAllocated qd is reduced by maximum packet size. QdQd qdqd JdJd Data expected to arrive length(s): length of subqueue of current existed data; PreAllocated s : length of data expected to arrive in the future

Network model: receiver behavior After the lifetime is expired, the receiver does: Reduce the rate of sending interests, following an AIMD (additive increase, multiplicative decrease) congestion control principle similar to TCP. May optionally re-request the data. Adjusting lifetime is not considered to be a proper congestion reaction action. 11

Evaluation (1) Deadline-based resource management model is analyzed using ndnSIM, conducting simulations on dumbbell topology. 12

Evaluation (2) 13 The variation in the 3(a) average RTT 3(b) number of dropped packets 3(c) number of received packets We have chosen 3 different cases in which lifetime is set either to 200 milliseconds or 1 second, while the bottleneck link capacity is set to either 1 Mbps or 500 Kbps. content transfer operations can tolerate different range of RTTs the number of dropped packets increases as the deadline is set to the lower values. if there is sufficient network capacity, the deadline setting does not have significant effect on the transmission performance

Evaluation (3) 14 Number of received packets 4(a) with FIFO style scheduling 4(b) with LIFO style scheduling 4(c) with deadline-based scheduled queues Next we will use three different traffic models. Type A traffic has 1000 ms packet lifetime with retransmissions for missing packets; type B with 200 ms lifetime with retransmissions; and type C with 200 ms lifetime, but without retransmissions. Devastating effect on the content with short lifetimes Scheduling the different traffic classes are treated more equally. Gives most capacity on the packets with short lifetimes.

Evaluation (4) 15 Number of expired interests (a) with FIFO style scheduling (b) with LIFO style scheduling (c) with deadline-based scheduled queues.

Conclusion In this paper we propose a new approach to network resource management, leveraging packet lifetimes. It makes the network management independent of RTT measurement, in conditions where RTT measurement is not proper, such as ICN. A scheduling algorithm that makes use of packet lifetimes is presented, trying to ensure packets are delivered within their assigned lifetimes. The proposal is compared with other scheduling algorithms based on NS-3 simulations. 16