Honeycomb: Enabling Structured DHTs to Support High Performance Applications

1. Honeycomb: Enabling Structured DHTs to Support High Performance Applications Venugopalan Ramasubramanian Yeejiun Song Emin Gün Sirer Cornell University

2. introduction • structured DHTs show great promise to run infrastructure services • self-organization, failure resilience • yet have limited deployment and application • performance is constrained by DHT structure and choice of parameters • Honeycomb: • broad class of DHTs that use prefix-matching • supports applications with widely different characteristics • adapts automatically to workload changes

3. proactive caching (1/2) • analysis-driven proactive caching • achieve O(1) average lookup latency, even less than one hop • optimize resource consumption by leveraging object popularity • Beehive supports only Zipf distributions, and does not incorporate object-specific overhead • Honeycomb eliminates these limitations • support any popularity distribution • incorporate fine-grained overhead, such as, object size and update rate

4. proactive caching (2/2) • computational technique to obtain optimal solutions • O(M logM) running time algorithm for M objects • optimal within one object • caches at the most one object more than optimal • significant decrease in resource consumption • 2.33 times less for web with object size • 6.54 times less for DNS with update rate

5. dynamic adaptation • workloads change rapidly during flash-crowds and denial of service attacks • periodic monitoring incurs long response time • one value of parameter unsuitable for all objects • monitor at a period proportional to the query rate • react to flash-crowds within minutes • independently set monitoring rate for each object • reduces overhead of monitoring

6. summary • Honeycomb is a self-adaptive framework for achieving high performance on prefix-based DHTs • broad-class of applications • cooperative web caching • content distribution • publish-subscribe • domain name system