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Salman A Avestimehr - One of the best experts on this subject based on the ideXlab platform.

  • characterizing the rate memory tradeoff in cache networks within a factor of 2
    IEEE Transactions on Information Theory, 2019
    Co-Authors: Qian Yu, Mohammad Ali Maddahali, Salman A Avestimehr
    Abstract:

    We consider a basic caching system, where a single server with a database of $N$ files (e.g., movies) is connected to a set of $K$ users through a shared Bottleneck Link. Each user has a local cache memory with a size of $M$ files. The system operates in two phases: a placement phase, where each cache memory is populated up to its size from the database, and a following delivery phase, where each user requests a file from the database, and the server is responsible for delivering the requested contents. The objective is to design the two phases to minimize the load (peak or average) of the Bottleneck Link. We characterize the rate-memory tradeoff of the above caching system within a factor of 2.00884 for both the peak rate and the average rate (under uniform file popularity), improving the state of the arts that are within a factor of 4 and 4.7, respectively. Moreover, in a practically important case where the number of files ( $N$ ) is large, we exactly characterize the tradeoff for systems with no more than five users and characterize the tradeoff within a factor of 2 otherwise. To establish these results, we develop two new converse bounds that improve over the state of the art.

  • the exact rate memory tradeoff for caching with uncoded prefetching
    IEEE Transactions on Information Theory, 2018
    Co-Authors: Qian Yu, Mohammad Ali Maddahali, Salman A Avestimehr
    Abstract:

    We consider a basic cache network, in which a single server is connected to multiple users via a shared Bottleneck Link. The server has a database of files (content). Each user has an isolated memory that can be used to cache content in a prefetching phase. In a following delivery phase, each user requests a file from the database, and the server needs to deliver users’ demands as efficiently as possible by taking into account their cache contents. We focus on an important and commonly used class of prefetching schemes, where the caches are filled with uncoded data. We provide the exact characterization of the rate-memory tradeoff for this problem, by deriving both the minimum average rate (for a uniform file popularity) and the minimum peak rate required on the Bottleneck Link for a given cache size available at each user. In particular, we propose a novel caching scheme, which strictly improves the state of the art by exploiting commonality among user demands. We then demonstrate the exact optimality of our proposed scheme through a matching converse, by dividing the set of all demands into types, and showing that the placement phase in the proposed caching scheme is universally optimal for all types. Using these techniques, we also fully characterize the rate-memory tradeoff for a decentralized setting, in which users fill out their cache content without any coordination.

  • characterizing the rate memory tradeoff in cache networks within a factor of 2
    International Symposium on Information Theory, 2017
    Co-Authors: Qian Yu, Mohammad Ali Maddahali, Salman A Avestimehr
    Abstract:

    We consider a basic caching system, where a single server with a database of N files (e.g. movies) is connected to a set of K users through a shared Bottleneck Link. Each user has a local cache memory with a size of M files. The system operates in two phases: a placement phase, where each cache memory is populated up to its size from the database, and a following delivery phase, where each user requests a file from the database, and the server is responsible for delivering the requested contents. The objective is to design the two phases to minimize the load (peak or average) of the Bottleneck Link. We characterize the rate-memory tradeoff of the above caching system within a factor of 2.00884 for both the peak rate and the average rate (under uniform file popularity), where the best proved characterization in the current literature gives a factor of 4 and 4.7 respectively. Moreover, in the practically important case where the number of files (N) is large, we exactly characterize the tradeoff for systems with no more than 5 users, and characterize the tradeoff within a factor of 2 otherwise. We establish these results by developing novel information theoretic outer-bounds for the caching problem, which improves the state of the art and gives tight characterization in various cases.

  • the exact rate memory tradeoff for caching with uncoded prefetching
    International Symposium on Information Theory, 2017
    Co-Authors: Qian Yu, Mohammad Ali Maddahali, Salman A Avestimehr
    Abstract:

    We consider a cache network, where a single server is connected to multiple users via a shared Bottleneck Link. The server has a set of files, which can be cached by each user in a prefetching phase. In a following delivery phase, each user requests a file and the server delivers user demands as efficiently as possible by taking into account their cache contents. We focus on an important and commonly used class of prefetching schemes, where the caches are filled with uncoded data. We provide the exact characterization of rate-memory tradeoff for this problem, by deriving both the minimum average rate (for a uniform file popularity) and the minimum peak rate required on the Bottleneck Link for a given cache size available at each user. We propose a novel caching scheme, which strictly improves the state of the art by exploiting commonality among user demands. We then demonstrate the exact optimality of our proposed scheme through a matching converse, by dividing the set of all demands into types, and showing that the placement phase in the proposed caching scheme is universally optimal for all types. Using these techniques, we can also fully characterize the rate-memory tradeoff for a decentralized setting, in which users fill out their cache content without coordination.

  • characterizing the rate memory tradeoff in cache networks within a factor of 2
    arXiv: Information Theory, 2017
    Co-Authors: Qian Yu, Mohammad Ali Maddahali, Salman A Avestimehr
    Abstract:

    We consider a basic caching system, where a single server with a database of $N$ files (e.g. movies) is connected to a set of $K$ users through a shared Bottleneck Link. Each user has a local cache memory with a size of $M$ files. The system operates in two phases: a placement phase, where each cache memory is populated up to its size from the database, and a following delivery phase, where each user requests a file from the database, and the server is responsible for delivering the requested contents. The objective is to design the two phases to minimize the load (peak or average) of the Bottleneck Link. We characterize the rate-memory tradeoff of the above caching system within a factor of $2.00884$ for both the peak rate and the average rate (under uniform file popularity), improving state of the arts that are within a factor of $4$ and $4.7$ respectively. Moreover, in a practically important case where the number of files ($N$) is large, we exactly characterize the tradeoff for systems with no more than $5$ users, and characterize the tradeoff within a factor of $2$ otherwise. To establish these results, we develop two new converse bounds that improve over the state of the art.

Qian Yu - One of the best experts on this subject based on the ideXlab platform.

  • characterizing the rate memory tradeoff in cache networks within a factor of 2
    IEEE Transactions on Information Theory, 2019
    Co-Authors: Qian Yu, Mohammad Ali Maddahali, Salman A Avestimehr
    Abstract:

    We consider a basic caching system, where a single server with a database of $N$ files (e.g., movies) is connected to a set of $K$ users through a shared Bottleneck Link. Each user has a local cache memory with a size of $M$ files. The system operates in two phases: a placement phase, where each cache memory is populated up to its size from the database, and a following delivery phase, where each user requests a file from the database, and the server is responsible for delivering the requested contents. The objective is to design the two phases to minimize the load (peak or average) of the Bottleneck Link. We characterize the rate-memory tradeoff of the above caching system within a factor of 2.00884 for both the peak rate and the average rate (under uniform file popularity), improving the state of the arts that are within a factor of 4 and 4.7, respectively. Moreover, in a practically important case where the number of files ( $N$ ) is large, we exactly characterize the tradeoff for systems with no more than five users and characterize the tradeoff within a factor of 2 otherwise. To establish these results, we develop two new converse bounds that improve over the state of the art.

  • the exact rate memory tradeoff for caching with uncoded prefetching
    IEEE Transactions on Information Theory, 2018
    Co-Authors: Qian Yu, Mohammad Ali Maddahali, Salman A Avestimehr
    Abstract:

    We consider a basic cache network, in which a single server is connected to multiple users via a shared Bottleneck Link. The server has a database of files (content). Each user has an isolated memory that can be used to cache content in a prefetching phase. In a following delivery phase, each user requests a file from the database, and the server needs to deliver users’ demands as efficiently as possible by taking into account their cache contents. We focus on an important and commonly used class of prefetching schemes, where the caches are filled with uncoded data. We provide the exact characterization of the rate-memory tradeoff for this problem, by deriving both the minimum average rate (for a uniform file popularity) and the minimum peak rate required on the Bottleneck Link for a given cache size available at each user. In particular, we propose a novel caching scheme, which strictly improves the state of the art by exploiting commonality among user demands. We then demonstrate the exact optimality of our proposed scheme through a matching converse, by dividing the set of all demands into types, and showing that the placement phase in the proposed caching scheme is universally optimal for all types. Using these techniques, we also fully characterize the rate-memory tradeoff for a decentralized setting, in which users fill out their cache content without any coordination.

  • characterizing the rate memory tradeoff in cache networks within a factor of 2
    International Symposium on Information Theory, 2017
    Co-Authors: Qian Yu, Mohammad Ali Maddahali, Salman A Avestimehr
    Abstract:

    We consider a basic caching system, where a single server with a database of N files (e.g. movies) is connected to a set of K users through a shared Bottleneck Link. Each user has a local cache memory with a size of M files. The system operates in two phases: a placement phase, where each cache memory is populated up to its size from the database, and a following delivery phase, where each user requests a file from the database, and the server is responsible for delivering the requested contents. The objective is to design the two phases to minimize the load (peak or average) of the Bottleneck Link. We characterize the rate-memory tradeoff of the above caching system within a factor of 2.00884 for both the peak rate and the average rate (under uniform file popularity), where the best proved characterization in the current literature gives a factor of 4 and 4.7 respectively. Moreover, in the practically important case where the number of files (N) is large, we exactly characterize the tradeoff for systems with no more than 5 users, and characterize the tradeoff within a factor of 2 otherwise. We establish these results by developing novel information theoretic outer-bounds for the caching problem, which improves the state of the art and gives tight characterization in various cases.

  • the exact rate memory tradeoff for caching with uncoded prefetching
    International Symposium on Information Theory, 2017
    Co-Authors: Qian Yu, Mohammad Ali Maddahali, Salman A Avestimehr
    Abstract:

    We consider a cache network, where a single server is connected to multiple users via a shared Bottleneck Link. The server has a set of files, which can be cached by each user in a prefetching phase. In a following delivery phase, each user requests a file and the server delivers user demands as efficiently as possible by taking into account their cache contents. We focus on an important and commonly used class of prefetching schemes, where the caches are filled with uncoded data. We provide the exact characterization of rate-memory tradeoff for this problem, by deriving both the minimum average rate (for a uniform file popularity) and the minimum peak rate required on the Bottleneck Link for a given cache size available at each user. We propose a novel caching scheme, which strictly improves the state of the art by exploiting commonality among user demands. We then demonstrate the exact optimality of our proposed scheme through a matching converse, by dividing the set of all demands into types, and showing that the placement phase in the proposed caching scheme is universally optimal for all types. Using these techniques, we can also fully characterize the rate-memory tradeoff for a decentralized setting, in which users fill out their cache content without coordination.

  • characterizing the rate memory tradeoff in cache networks within a factor of 2
    arXiv: Information Theory, 2017
    Co-Authors: Qian Yu, Mohammad Ali Maddahali, Salman A Avestimehr
    Abstract:

    We consider a basic caching system, where a single server with a database of $N$ files (e.g. movies) is connected to a set of $K$ users through a shared Bottleneck Link. Each user has a local cache memory with a size of $M$ files. The system operates in two phases: a placement phase, where each cache memory is populated up to its size from the database, and a following delivery phase, where each user requests a file from the database, and the server is responsible for delivering the requested contents. The objective is to design the two phases to minimize the load (peak or average) of the Bottleneck Link. We characterize the rate-memory tradeoff of the above caching system within a factor of $2.00884$ for both the peak rate and the average rate (under uniform file popularity), improving state of the arts that are within a factor of $4$ and $4.7$ respectively. Moreover, in a practically important case where the number of files ($N$) is large, we exactly characterize the tradeoff for systems with no more than $5$ users, and characterize the tradeoff within a factor of $2$ otherwise. To establish these results, we develop two new converse bounds that improve over the state of the art.

Mohammad Ali Maddahali - One of the best experts on this subject based on the ideXlab platform.

  • characterizing the rate memory tradeoff in cache networks within a factor of 2
    IEEE Transactions on Information Theory, 2019
    Co-Authors: Qian Yu, Mohammad Ali Maddahali, Salman A Avestimehr
    Abstract:

    We consider a basic caching system, where a single server with a database of $N$ files (e.g., movies) is connected to a set of $K$ users through a shared Bottleneck Link. Each user has a local cache memory with a size of $M$ files. The system operates in two phases: a placement phase, where each cache memory is populated up to its size from the database, and a following delivery phase, where each user requests a file from the database, and the server is responsible for delivering the requested contents. The objective is to design the two phases to minimize the load (peak or average) of the Bottleneck Link. We characterize the rate-memory tradeoff of the above caching system within a factor of 2.00884 for both the peak rate and the average rate (under uniform file popularity), improving the state of the arts that are within a factor of 4 and 4.7, respectively. Moreover, in a practically important case where the number of files ( $N$ ) is large, we exactly characterize the tradeoff for systems with no more than five users and characterize the tradeoff within a factor of 2 otherwise. To establish these results, we develop two new converse bounds that improve over the state of the art.

  • the exact rate memory tradeoff for caching with uncoded prefetching
    IEEE Transactions on Information Theory, 2018
    Co-Authors: Qian Yu, Mohammad Ali Maddahali, Salman A Avestimehr
    Abstract:

    We consider a basic cache network, in which a single server is connected to multiple users via a shared Bottleneck Link. The server has a database of files (content). Each user has an isolated memory that can be used to cache content in a prefetching phase. In a following delivery phase, each user requests a file from the database, and the server needs to deliver users’ demands as efficiently as possible by taking into account their cache contents. We focus on an important and commonly used class of prefetching schemes, where the caches are filled with uncoded data. We provide the exact characterization of the rate-memory tradeoff for this problem, by deriving both the minimum average rate (for a uniform file popularity) and the minimum peak rate required on the Bottleneck Link for a given cache size available at each user. In particular, we propose a novel caching scheme, which strictly improves the state of the art by exploiting commonality among user demands. We then demonstrate the exact optimality of our proposed scheme through a matching converse, by dividing the set of all demands into types, and showing that the placement phase in the proposed caching scheme is universally optimal for all types. Using these techniques, we also fully characterize the rate-memory tradeoff for a decentralized setting, in which users fill out their cache content without any coordination.

  • characterizing the rate memory tradeoff in cache networks within a factor of 2
    International Symposium on Information Theory, 2017
    Co-Authors: Qian Yu, Mohammad Ali Maddahali, Salman A Avestimehr
    Abstract:

    We consider a basic caching system, where a single server with a database of N files (e.g. movies) is connected to a set of K users through a shared Bottleneck Link. Each user has a local cache memory with a size of M files. The system operates in two phases: a placement phase, where each cache memory is populated up to its size from the database, and a following delivery phase, where each user requests a file from the database, and the server is responsible for delivering the requested contents. The objective is to design the two phases to minimize the load (peak or average) of the Bottleneck Link. We characterize the rate-memory tradeoff of the above caching system within a factor of 2.00884 for both the peak rate and the average rate (under uniform file popularity), where the best proved characterization in the current literature gives a factor of 4 and 4.7 respectively. Moreover, in the practically important case where the number of files (N) is large, we exactly characterize the tradeoff for systems with no more than 5 users, and characterize the tradeoff within a factor of 2 otherwise. We establish these results by developing novel information theoretic outer-bounds for the caching problem, which improves the state of the art and gives tight characterization in various cases.

  • the exact rate memory tradeoff for caching with uncoded prefetching
    International Symposium on Information Theory, 2017
    Co-Authors: Qian Yu, Mohammad Ali Maddahali, Salman A Avestimehr
    Abstract:

    We consider a cache network, where a single server is connected to multiple users via a shared Bottleneck Link. The server has a set of files, which can be cached by each user in a prefetching phase. In a following delivery phase, each user requests a file and the server delivers user demands as efficiently as possible by taking into account their cache contents. We focus on an important and commonly used class of prefetching schemes, where the caches are filled with uncoded data. We provide the exact characterization of rate-memory tradeoff for this problem, by deriving both the minimum average rate (for a uniform file popularity) and the minimum peak rate required on the Bottleneck Link for a given cache size available at each user. We propose a novel caching scheme, which strictly improves the state of the art by exploiting commonality among user demands. We then demonstrate the exact optimality of our proposed scheme through a matching converse, by dividing the set of all demands into types, and showing that the placement phase in the proposed caching scheme is universally optimal for all types. Using these techniques, we can also fully characterize the rate-memory tradeoff for a decentralized setting, in which users fill out their cache content without coordination.

  • characterizing the rate memory tradeoff in cache networks within a factor of 2
    arXiv: Information Theory, 2017
    Co-Authors: Qian Yu, Mohammad Ali Maddahali, Salman A Avestimehr
    Abstract:

    We consider a basic caching system, where a single server with a database of $N$ files (e.g. movies) is connected to a set of $K$ users through a shared Bottleneck Link. Each user has a local cache memory with a size of $M$ files. The system operates in two phases: a placement phase, where each cache memory is populated up to its size from the database, and a following delivery phase, where each user requests a file from the database, and the server is responsible for delivering the requested contents. The objective is to design the two phases to minimize the load (peak or average) of the Bottleneck Link. We characterize the rate-memory tradeoff of the above caching system within a factor of $2.00884$ for both the peak rate and the average rate (under uniform file popularity), improving state of the arts that are within a factor of $4$ and $4.7$ respectively. Moreover, in a practically important case where the number of files ($N$) is large, we exactly characterize the tradeoff for systems with no more than $5$ users, and characterize the tradeoff within a factor of $2$ otherwise. To establish these results, we develop two new converse bounds that improve over the state of the art.

M Ghanbari - One of the best experts on this subject based on the ideXlab platform.

  • fuzzy logic congestion control of transcoded video streaming without packet loss feedback
    IEEE Transactions on Circuits and Systems for Video Technology, 2008
    Co-Authors: Emmanuel Jammeh, Martin Fleury, M Ghanbari
    Abstract:

    Congestion control of a variable bit-rate video stream crossing the Internet is crucial to ensuring the quality of the received video. When a fuzzy-logic congestion controller (FLC) changes the sending rate of a video transcoder, it does so without feedback of packet loss, using packet dispersion instead. Compared with the well-known TFRC and RAP controllers, the FLC's sending rate is significantly smoother, allowing it to more closely take up available bandwidth at a Bottleneck Link. There is an accompanying order of magnitude reduction in packet losses. Due to better utilization of the available bandwidth, video quality is improved over time by several decibels in low-packet-loss conditions. The strength of the FLC solution is demonstrated by the resulting video quality when typical Web traffic forms the background traffic. The FLC avoids any risk of congestion collapse through fairness to coexisting TCP flows and is robust to changes in path delay and router buffer configuration.

  • router response to traffic at a Bottleneck Link
    Testbeds and Research Infrastructures for the DEvelopment of NeTworks and COMmunities, 2006
    Co-Authors: M Paredesfarrera, Martin Fleury, M Ghanbari
    Abstract:

    Traffic at varying bit rates, packet lengths and packet rates are passed across a Bottleneck Link. The router response is determined, especially the onset of instability due to excessive CPU load. The paper concludes that it is primarily packet rate that governs the router response. The results are relevant to multimedia streaming applications.

Jack Y. B. Lee - One of the best experts on this subject based on the ideXlab platform.

  • achieving high throughput and low delay by accurately regulating Link queue length over mobile data network
    Wireless and Mobile Computing Networking and Communications, 2014
    Co-Authors: Ke Liu, Jack Y. B. Lee
    Abstract:

    Knowledge of the queue length of the Bottleneck Link has many potential applications such as congestion control, traffic engineering, traffic policing, content adaptation, QoS monitoring and provisioning, etc. A recent work proposed a new Sum-of-Delay with Timestamp (SoD-TS) algorithm which can accurately estimate queue length in mobile networks with both bandwidth variations and upLink delay variations by exploiting the existing TCP Timestamp option. By making use of SoD-TS we developed a novel transport protocol - queue-length-aware TCP (TCP-QLA), that tackles the problem of bufferbloat to provide better QoS for applications requiring low end-to-end delay and/or high bandwidth utilization. Trace-driven simulation shows that compared to TCP CUBIC TCP QLA can reduce the RTT by a factor of 2.7 while still achieving over 97% bandwidth utilization. Moreover, TCP-QLA further reduces RTT by 50% compared to delay-based TCP such as FAST TCP and TCP Vegas.

  • On Queue Length and Link Buffer Size Estimation in 3G/4G Mobile Data Networks
    IEEE Transactions on Mobile Computing, 2014
    Co-Authors: Stanley C. F. Chan, K M Chan, Ke Liu, Jack Y. B. Lee
    Abstract:

    The emerging mobile data networks fueled by the world-wide deployment of 3G, HSPA, and LTE networks created new challenges for the development of Internet applications. Unlike their wired counterpart, mobile data networks are known to exhibit highly variable bandwidth. Moreover, base stations are often equipped with large buffers to absorb bandwidth fluctuations to prevent unnecessary packet losses. Consequently to optimize protocol performance in mobile data networks it is essential to be able to accurately characterize two key network properties: queue length and buffer size of the Bottleneck Link. This work tackles the challenge in estimating these two network properties in modern mobile data networks. Using extensive trace-driven simulations based on actual bandwidth trace data measured from production mobile data networks, we show that existing queue-length and Link buffer size estimation algorithms no longer work well in bandwidth-varying networks. We develop a novel sum-of-delays algorithm which incorporates the effect of bandwidth variations into its estimation. Extensive trace-driven simulation results show that it can accurately estimate the queue length and Link buffer size under both fixed and varying bandwidth conditions, outperforming existing algorithms by up to two orders of magnitude.