scispace - formally typeset
S

Shankaranarayanan Puzhavakath Narayanan

Researcher at AT&T Labs

Publications -  22
Citations -  158

Shankaranarayanan Puzhavakath Narayanan is an academic researcher from AT&T Labs. The author has contributed to research in topics: Cloud computing & Web page. The author has an hindex of 5, co-authored 22 publications receiving 132 citations. Previous affiliations of Shankaranarayanan Puzhavakath Narayanan include Purdue University.

Papers
More filters
Proceedings ArticleDOI

PARCEL: Proxy Assisted BRowsing in Cellular networks for Energy and Latency reduction

TL;DR: PARCEL splits functionality between the mobile device and the proxy based on their strengths, and in a manner distinct from both traditional browsers and existing cloud-heavy approaches, and results show PARCEL continues to perform well under client interactions, owing to its judicious functionality split.
Proceedings ArticleDOI

Reducing Latency Through Page-aware Management of Web Objects by Content Delivery Networks

TL;DR: This paper explores page-structure-aware strategies for placing objects in CDN cache hierarchies and presents schemes for identifying these objects and develop mechanisms to ensure that they are served with higher priority by the CDN, while balancing traditional CDN concerns such as optimizing the delivery of popular objects and minimizing bandwidth costs.

Toward Session Consistency for the Edge

TL;DR: A distributed datastore tailored for edge computing that provides session consistency between otherwise eventual consistent replicas by tracking and migrating only the clientaffected keys between the replicas.
Proceedings ArticleDOI

NutShell: Scalable Whittled Proxy Execution for Low-Latency Web over Cellular Networks

TL;DR: Experiments with top Alexa Web pages show NutShell can sustain, on average, 27\% more user requests per second than a proxy performing fully redundant execution, while preserving, and sometimes enhancing, the latency benefits.
Journal ArticleDOI

Karma: Cost-Effective Geo-Replicated Cloud Storage with Dynamic Enforcement of Causal Consistency

TL;DR: Karma is proposed, the first system to enable causal consistency for partitioned data stores while achieving the cost advantages of partial replication without the availability and latency problems of the simple extension.