Akamai Technologies

About: Akamai Technologies is a company organization based out in Cambridge, Massachusetts, United States. It is known for research contribution in the topics: Server & Content delivery network. The organization has 462 authors who have published 569 publications receiving 33540 citations. The organization is also known as: Akamai Technologies, Inc..

Understanding the mirai botnet

Abstract: The Mirai botnet, composed primarily of embedded and IoT devices, took the Internet by storm in late 2016 when it overwhelmed several high-profile targets with massive distributed denial-of-service (DDoS) attacks. In this paper, we provide a seven-month retrospective analysis of Mirai's growth to a peak of 600k infections and a history of its DDoS victims. By combining a variety of measurement perspectives, we analyze how the botnet emerged, what classes of devices were affected, and how Mirai variants evolved and competed for vulnerable hosts. Our measurements serve as a lens into the fragile ecosystem of IoT devices. We argue that Mirai may represent a sea change in the evolutionary development of botnets--the simplicity through which devices were infected and its precipitous growth, demonstrate that novice malicious techniques can compromise enough low-end devices to threaten even some of the best-defended targets. To address this risk, we recommend technical and nontechnical interventions, as well as propose future research directions.

FAST TCP: motivation, architecture, algorithms, performance

Abstract: We describe FAST TCP, a new TCP congestion control algorithm for high-speed long-latency networks, from design to implementation. We highlight the approach taken by FAST TCP to address the four difficulties which the current TCP implementation has at large windows. We describe the architecture and summarize some of the algorithms implemented in our prototype. We characterize its equilibrium and stability properties. We evaluate it experimentally in terms of throughput, fairness, stability, and responsiveness

System and method for delivery of video data over a computer network

Abstract: A video clip storage and retrieval system whereby video clips, stored locally and/or at a more remote location, can be requested and retrieved by a user at the user's multimedia terminal. When the user requests a desired video clip, the request is processed by a primary index manager ("PIM") via a Local Search and Retrieval Unit ("SRU"). Before the message is communicated to the PIM, the local SRU checks its own storage to see whether the requested video clips are available locally. If some of the video clips are local, the local SRU still forwards the request to the PIM so that the PIM may determine specific video clip usage. The PIM determines the extended SRU where the audio-visual data is stored and passes this information to a Data Sequencing Interface ("DSI"). The DSI collects the video clips and downloads the clips to the user's terminal. The user may then view, copy, or print the video clip as desired. In a preferred embodiment, a distributed digital video clip delivery system, according to the invention, provides video clips stored at local and/or remote locations, which can be requested from the Internet and retrieved at the user's multimedia terminal. When the user requests a desired video clip shown on a Web page, the request is diverted to a primary index manager ("PIM"). The PIM attempts to locate the closest server containing the requested clip, from which the download is completed. The system further includes means for uploading and distributing clips to geographically diverse servers, dynamic load balancing, subscription management mechanisms, and protection means to discourage unauthorized duplication of video clips.

Cutting the electric bill for internet-scale systems

Abstract: Energy expenses are becoming an increasingly important fraction of data center operating costs. At the same time, the energy expense per unit of computation can vary significantly between two different locations. In this paper, we characterize the variation due to fluctuating electricity prices and argue that existing distributed systems should be able to exploit this variation for significant economic gains. Electricity prices exhibit both temporal and geographic variation, due to regional demand differences, transmission inefficiencies, and generation diversity. Starting with historical electricity prices, for twenty nine locations in the US, and network traffic data collected on Akamai's CDN, we use simulation to quantify the possible economic gains for a realistic workload. Our results imply that existing systems may be able to save millions of dollars a year in electricity costs, by being cognizant of locational computation cost differences.

Nearly-linear time algorithms for graph partitioning, graph sparsification, and solving linear systems

Abstract: We present algorithms for solving symmetric, diagonally-dominant linear systems to accuracy e in time linear in their number of non-zeros and log (κf (A) e), where κf (A) is the condition number of the matrix defining the linear system. Our algorithm applies the preconditioned Chebyshev iteration with preconditioners designed using nearly-linear time algorithms for graph sparsification and graph partitioning.