Sublinear Algorithms for Big Data Applications (SpringerBriefs in Computer Science)

The brief focuses on applying sublinear algorithms to manage critical big data challenges. The text offers an essential introduction to sublinear algorithms, explaining why they are vital to large scale data systems. It also demonstrates how to apply sublinear algorithms to three familiar big data applications: wireless sensor networks, big data processing in Map Reduce and smart grids. These applications present common experiences, bridging the theoretical advances of sublinear algorithms and the application domain. Sublinear Algorithms for Big Data Applications is suitable for researchers, engineers and graduate students in the computer science, communications and signal processing communities.

這份簡報著重於將次線性演算法應用於處理重要的大數據挑戰。本文提供了對次線性演算法的基本介紹，解釋了為何它們對於大規模數據系統至關重要。同時，它還展示了如何將次線性演算法應用於三個常見的大數據應用領域：無線感測網絡、Map Reduce中的大數據處理和智能電網。這些應用案例提供了將次線性演算法的理論進展與應用領域相結合的共同經驗。《次線性演算法應用於大數據應用》適合計算機科學、通信和信號處理社區的研究人員、工程師和研究生閱讀。