Suparna Bhattacharya

Coordinating backup/recovery and data consistency between database and file systems

Managing a combined store consisting of database data and file data in a robust and consistent manner is a challenge for database systems and content management systems. In such a hybrid system, images, videos, engineering drawings, etc. are stored as files on a file server while meta-data referencing/indexing such files is created and stored in a relational database to take advantage of efficient search. In this paper we describe solutions for two potentially problematic aspects of such a data management system: backup/recovery and data consistency. We present algorithms for performing backup and recovery of the DBMS data in a coordinated fashion with the files on the file servers. Our algorithms for coordinated backup and recovery have been implemented in the IBM DB2/DataLinks product [1]. We also propose an efficient solution to the problem of maintaining consistency between the content of a file and the associated meta-data stored in the DBMS from a readers point of view without holding long duration locks on meta-data tables. In the model, an object is directly accessed and edited in-place through normal file system APIs using a reference obtained via an SQL Query on the database. To relate file modifications to meta-data updates, the user issues an update through the DBMS, and commits both file and meta-data updates together.

Effective switch memory management in OpenFlow networks

OpenFlow networks require installation of flow rules in a limited capacity switch memory (Ternary Content Addressable Memory or TCAMs, in particular) from a logically centralized controller. A controller can manage the switch memory in an OpenFlow network through events that are generated by the switch at discrete time intervals. Recent studies have shown that data centers can have up to 10,000 network flows per second per server rack today. Increasing the TCAM size to accommodate these large number of flow rules is not a viable solution since TCAM is costly and power hungry. Current OpenFlow controllers handle this issue by installing flow rules with a default idle timeout after which the switch automatically evicts the rule from its TCAM. This results in inefficient usage of switch memory for short lived flows when the timeout is too high and in increased controller workload for frequent flows when the timeout is too low. In this context, we present SmartTime - an OpenFlow controller system that combines an adaptive timeout heuristic to compute efficient idle timeouts with proactive eviction of flow rules, which results in effective utilization of TCAM space while ensuring that TCAM misses (or controller load) does not increase. To the best of our knowledge, SmartTime is the first real implementation of an intelligent flow management strategy in an OpenFlow controller that can be deployed in current OpenFlow networks. In our experiments using multiple real data center packet traces and cache sizes, SmartTime adaptive policy consistently outperformed the best performing static idle timeout policy or random eviction policy by up to 58% in terms of total cost.

Software Bloat and Wasted Joules: Is Modularity a Hurdle to Green Software?

The paper discusses that adopting an integrated analysis of software bloat and hardware platforms is necessary to realizing modular software thats also green.

The interplay of software bloat, hardware energy proportionality and system bottlenecks

In large flexible software systems, bloat occurs in many forms, causing excess resource utilization and resource bottlenecks. This results in lost throughput and wasted joules. However, mitigating bloat is not easy; efforts are best applied where savings would be substantial. To aid this we develop an analytical model establishing the relation between bottleneck in resources, bloat, performance and power. Analyses with the model places into perspective results from the first experimental study of the power-performance implications of bloat. In the experiments we find that while bloat reduction can provide as much as 40% energy savings, the degree of impact depends on hardware and software characteristics. We confirm predictions from our model with selected results from our experimental study. Our findings show that a software-only view is inadequate when assessing the effects of bloat. The impact of bloat on physical resource usage and power should be understood for a full systems perspective to properly deploy bloat reduction solutions and reap their power-performance benefits.

Combining concern input with program analysis for bloat detection

Framework based software tends to get bloated by accumulating optional features (or concerns) just-in-case they are needed. The good news is that such feature bloat need not always cause runtime execution bloat. The bad news is that often enough, only a few statements from an optional concern may cause execution bloat that may result in as much as 50% runtime overhead. We present a novel technique to analyze the connection between optional concerns and the potential sources of execution bloat induced by them. Our analysis automatically answers questions such as (1) whether a given set of optional concerns could lead to execution bloat and (2) which particular statements are the likely sources of bloat when those concerns are not required. The technique combines coarse grain concern input from an external source with a fine-grained static analysis. Our experimental evaluation highlights the effectiveness of such concern augmented program analysis in execution bloat assessment of ten programs.

Enterprise context: a rich source of requirements for context-oriented programming

We introduce the domain of enterprise context, as opposed to personal or execution context, and we present requirements for context-oriented programming technology arising out of this broader notion of context. We illustrate enterprise context with scenarios in which data from across an enterprise, as well as data from outside an enterprise, are all brought to bear as context in any situation where they are relevant and can factor into making better decisions and achieving better outcomes. We suggest enterprise context as a rich source of requirements for context-oriented programming models, languages, and virtual machines. In particular, we raise issues such as scale, integration, relevance, temporality, protection, privacy, provenance, policy in general, and valuation. And, for this workshop, we propose enterprise context as one perspective for discussion of new language and VM features: How do proposed features support such a domain?

Chemiresistive gas sensing characteristics of cobalt oxide thin films

We report synthesis of 100 nm thick cobalt oxide films – prepared by electron-beam evaporation of Co onto quartz (Q- films) and c-plane sapphire substrate (S- films) followed by oxygen annealing. Films have been characterized for their structure and morphology by using X-ray Diffraction (XRD) and Scanning Electron Microscopy (SEM). The prepared films have been investigated for their chemiresistive gas sensing characteristics for a host of test gases (CH4, CO, NO2, Cl2, NH3 and H2S) as a function of operating temperature (between 50 and 350°C) and gas concentration (3-30 ppm). We demonstrate that both Q and S-films are highly selective to H2S at an operating temperature of 250°C. However it has been observed that films prepared on sapphire show much less base resistance drift as compared to the films on quartz substrate.