Self-* overload control for distributed web systems

Unexpected increases in demand and most of all flash crowds are considered the bane of every web application as they may cause intolerable delays or even service unavailability. Proper quality of service policies must guarantee rapid reactivity and responsiveness even in such critical situations. Previous solutions fail to meet common performance requirements when the system has to face sudden and unpredictable surges of traffic. Indeed they often rely on a proper setting of key parameters which requires laborious manual tuning, preventing a fast adaptation of the control policies. We contribute an original Self-* Overload Control (SOC) policy. This allows the system to self-configure a dynamic constraint on the rate of admitted sessions in order to respect service level agreements and maximize the resource utilization at the same time. Our policy does not require any prior information on the incoming traffic or manual configuration of key parameters. We ran extensive simulations under a wide range of operating conditions, showing that SOC rapidly adapts to time varying traffic and self-optimizes the resource utilization. It admits as many new sessions as possible in observance of the agreements, even under intense workload variations. We compared our algorithm to previously proposed approaches highlighting a more stable behavior and a better performance.Comment: The full version of this paper, titled "Self-* through self-learning: overload control for distributed web systems", has been published on Computer Networks, Elsevier. The simulator used for the evaluation of the proposed algorithm is available for download at the address: http://www.dsi.uniroma1.it/~novella/qos_web

Prediction-Based Energy Saving Mechanism in 3GPP NB-IoT Networks

The current expansion of the Internet of things (IoT) demands improved communication platforms that support a wide area with low energy consumption. The 3rd Generation Partnership Project introduced narrowband IoT (NB-IoT) as IoT communication solutions. NB-IoT devices should be available for over 10 years without requiring a battery replacement. Thus, a low energy consumption is essential for the successful deployment of this technology. Given that a high amount of energy is consumed for radio transmission by the power amplifier, reducing the uplink transmission time is key to ensure a long lifespan of an IoT device. In this paper, we propose a prediction-based energy saving mechanism (PBESM) that is focused on enhanced uplink transmission. The mechanism consists of two parts: first, the network architecture that predicts the uplink packet occurrence through a deep packet inspection; second, an algorithm that predicts the processing delay and pre-assigns radio resources to enhance the scheduling request procedure. In this way, our mechanism reduces the number of random accesses and the energy consumed by radio transmission. Simulation results showed that the energy consumption using the proposed PBESM is reduced by up to 34% in comparison with that in the conventional NB-IoT method

EVEREST IST - 2002 - 00185 : D23 : final report

Deliverable públic del projecte europeu EVERESTThis deliverable constitutes the final report of the project IST-2002-001858 EVEREST. After its successful completion, the project presents this document that firstly summarizes the context, goal and the approach objective of the project. Then it presents a concise summary of the major goals and results, as well as highlights the most valuable lessons derived form the project work. A list of deliverables and publications is included in the annex.Postprint (published version

WebWave: Globally Load Balanced Fully Distributed Caching of Hot Published Documents

Document publication service over such a large network as the Internet challenges us to harness available server and network resources to meet fast growing demand. In this paper, we show that large-scale dynamic caching can be employed to globally minimize server idle time, and hence maximize the aggregate server throughput of the whole service. To be efficient, scalable and robust, a successful caching mechanism must have three properties: (1) maximize the global throughput of the system, (2) find cache copies without recourse to a directory service, or to a discovery protocol, and (3) be completely distributed in the sense of operating only on the basis of local information. In this paper, we develop a precise definition, which we call tree load-balance (TLB), of what it means for a mechanism to satisfy these three goals. We present an algorithm that computes TLB off-line, and a distributed protocol that induces a load distribution that converges quickly to a TLB one. Both algorithms place cache copies of immutable documents, on the routing tree that connects the cached document's home server to its clients, thus enabling requests to stumble on cache copies en route to the home server.Harvard University; The Saudi Cultural Mission to the U.S.A

Managing community membership information in a small-world grid

As the Grid matures the problem of resource discovery across communities, where resources now include computational services, is becoming more critical. The number of resources available on a world-wide grid is set to grow exponentially in much the same way as the number of static web pages on the WWW. We observe that the world-wide resource discovery problem can be modelled as a slowly evolving very-large sparse-matrix where individual matrix elements represent nodes’ knowledge of one another. Blocks in the matrix arise where nodes offer more than one service. Blocking effects also arise in the identification of sub-communities in the Grid. The linear algebra community has long been aware of suitable representations of large, sparse matrices. However, matrices the size of the world-wide grid potentially number in the billions, making dense solutions completely intractable. Distributed nodes will not necessarily have the storage capacity to store the addresses of any significant percentage of the available resources. We discuss ways of modelling this problem in the regime of a slowly changing service base including phenomena such as percolating networks and small-world network effects

CASPR: Judiciously Using the Cloud for Wide-Area Packet Recovery

We revisit a classic networking problem -- how to recover from lost packets in the best-effort Internet. We propose CASPR, a system that judiciously leverages the cloud to recover from lost or delayed packets. CASPR supplements and protects best-effort connections by sending a small number of coded packets along the highly reliable but expensive cloud paths. When receivers detect packet loss, they recover packets with the help of the nearby data center, not the sender, thus providing quick and reliable packet recovery for latency-sensitive applications. Using a prototype implementation and its deployment on the public cloud and the PlanetLab testbed, we quantify the benefits of CASPR in providing fast, cost effective packet recovery. Using controlled experiments, we also explore how these benefits translate into improvements up and down the network stack