Performance of in-memory key-value store (KVS) continues to be of great importance as
modern KVS goes beyond the traditional object-caching workload and becomes a key …

As an emerging technology, blockchain has achieved great success in numerous
application scenarios, from intelligent healthcare to smart cities. However, a long-standing …

Modern data appliances face severe bandwidth bottlenecks when moving vast amounts of
data from storage to the query processing nodes. A possible solution to mitigate these …

The ever increasing amount of data being handled in data centers causes an intrinsic
inefficiency: moving data around is expensive in terms of bandwidth, latency, and power …

Consensus mechanisms for ensuring consistency are some of the most expensive
operations in managing large amounts of data. Often, there is a trade off that involves …

Non-relational database systems (NRDS) such as graph and key-value have gained
attention in various trending business and analytical application domains. However, while …

This paper tackles the challenges of obtaining more efficient data center computing while
maintaining low latency, low cost, programmability, and the potential for workload …

MapReduce, originally developed by Google for search applications, has recently become a
popular programming framework for parallel and distributed environments. This paper …

TCP/IP is widely used both in the Internet as well as in data centers. The protocol makes
very few assumptions about the underlying network and provides useful guarantees such as …

Conventional radix-tree page tables have scalability challenges, as address translation
following a TLB miss potentially requires multiple memory accesses in sequence. An …