Praveen Jayachandran

SATIRE: a software architecture for smart AtTIRE

Personal instrumentation and monitoring services that collect and archive the physical activities of a user have recently been introduced for various medical, personal, safety, and entertainment purposes. A general software architecture is needed to support different categories of such monitoring services. This paper presents a software architecture, implementation, and preliminary evaluation of SATIRE, a wearable personal monitoring service transparently embedded in user garments. SATIRE records the owners activity and location for subsequent automated uploading and archiving. The personal archive can later be searched for particular events to answer questions regarding past and present user activity, location, and behavior patterns. A short feasibility and usage study of a prototype based on MicaZ motes provides a proof of concept for the SATIRE architecture.

Datalink streaming in wireless sensor networks

Datalink layer framing in wireless sensor networks usually faces a trade-off between large frame sizes for high channel bandwidth utilization and small frame sizes for effective error recovery. Given the high error rates of intermote communications, TinyOS opts in favor of small frame sizes at the cost of extremely low channel bandwidth utilization. In this paper, we describe Seda: a streaming datalink layer that resolves the above dilemma by decoupling framing from error recovery. Seda treats the packets from the upper layer as a continuous stream of bytes. It breaks the data stream into blocks, and retransmits erroneous blocks only (as opposed to the entire erroneous frame). Consequently, the frame-error-rate (FER), the main factor that bounds the frame size in the current design, becomes irrelevant to error recovery. A frame can therefore be sufficiently large in great favor of high utilization of the wireless channel bandwidth, without compromising the effectiveness of error recovery. Meanwhile, the size of each block is configured according to the error characteristics of the wireless channel to optimize the performance of error recovery. Seda has been implemented as a new datalink layer in the TinyOS, and evaluated through both simulations and experiments in a testbed of 48 MicaZ motes. Our results show that, by increasing the TinyOS frame size from the default 29 bytes to 100 bytes (limited by the buffer space at MicaZ firmware), Seda improves the throughput around 25% under typical wireless channel conditions. Seda also reduces the retransmission traffic volume by more than 50%, compared to a framebased retransmission scheme. Our analysis also exposes that future sensor motes should be equipped with radios with more packet buffer space on the radio firmware to achieve optimal utilization of the channel capacity.

ANDES: An ANalysis-Based DEsign Tool for Wireless Sensor Networks

We have developed an analysis-based design tool, ANDES, for modeling a wireless sensor network system and analyzing its performance before deployment ANDES enables designers to systematically develop a model for the system, refine it iteratively by tuning the system parameters based on existing analysis techniques, and resolve key design decisions according to the required system performance. We also present a real-time communication schedulability analysis for sensor networks based on exact characterization which utilizes information regarding network topology and workload characteristics to analyze the schedulability of a set of periodic streams with real-time constraints. We further demonstrate the use of ANDES for the designers through detailed case studies where we design wireless sensor network applications (for target detection and environmental monitoring) using ANDES and validate the results through simulations. Currently, ANDES supports communication schedulability analysis, target tracking analysis and real-time capacity analysis which work on system models with differing levels of detail. ANDES has been developed by extending the AADL/OSATE framework which has been used extensively for real-time and embedded systems. Based on key insights gained from the development of this analysis tool, we address issues in AADL for its use in the field of wireless sensor networks. We have developed a plug-in for ANDES, called ModelGeneration, which bridges the gap between the semantics needed for sensor networks and the syntax supported by AADL. This makes it easy for sensor network designers to build system models that are intuitive to them. Furthermore, ANDES is extensible and new analysis techniques can be easily incorporated into the toolset.

CloudPD: Problem determination and diagnosis in shared dynamic clouds

In this work, we address problem determination in virtualized clouds. We show that high dynamism, resource sharing, frequent reconfiguration, high propensity to faults and automated management introduce significant new challenges towards fault diagnosis in clouds. Towards this, we propose CloudPD, a fault management framework for clouds. CloudPD leverages (i) a canonical representation of the operating environment to quantify the impact of sharing; (ii) an online learning process to tackle dynamism; (iii) a correlation-based performance models for higher detection accuracy; and (iv) an integrated end-to-end feedback loop to synergize with a cloud management ecosystem. Using a prototype implementation with cloud representative batch and transactional workloads like Hadoop, Olio and RUBiS, it is shown that CloudPD detects and diagnoses faults with low false positives (<; 16%) and high accuracy of 88%, 83% and 83%, respectively. In an enterprise trace-based case study, CloudPD diagnosed anomalies within 30 seconds and with an accuracy of 77%, demonstrating its effectiveness in real-life operations.

Delay Composition Algebra: A Reduction-Based Schedulability Algebra for Distributed Real-Time Systems

This paper presents the delay composition algebra: a set of simple operators for systematic transformation of distributed real-time task systems into single-resource task systems such that schedulability properties of the original system are preserved. The transformation allows performing schedulability analysis on distributed systems using uniprocessor theory and analysis tools. Reduction-based analyses techniques have been used in other contexts such as control theory and circuit theory, by defining rules to compose together components of the system and reducing them into equivalent single components that can be easily analyzed. This paper is the first to develop such reduction rules for distributed real-time systems. By successively applying operators such as PIPE and SPLIT on operands that represent workload on composed subsystems, we show how a distributed task system can be reduced to an equivalent single resource task set from which the end-to-end delay and schedulability of tasks can be inferred. We show through simulations that the proposed analysis framework is less pessimistic with increasing system scale compared to traditional approaches.

Minimizing End-to-End Delay in Wireless Networks Using a Coordinated EDF Schedule

We study the end-to-end delay bounds that can be achieved in wireless networks using packet deadlines. We assume a set of flows in the network, for which flow i has burst parameter &#963;_i, injection rate &#961;_i, and path length K_i. It was already known that, in wireline networks, the Coordinated-Earliest-Deadline-First (CEDF) protocol can achieve and end-to-end delay of approximately (&#963;_i/&#961;_i)+K_i, whereas other schedulers such as Weighted Fair Queuing, have end-to-end delay bounds of the form (&#963;_i + Ki)/&#961;_i. For the case of wireless networks of arbitrary topology, the focus has typically been more on throughput optimality than minimizing delay. In this paper, we study the delay bounds that can be achieved by combining wireless link scheduling algorithms with a CEDF packet scheduler. We first present a centralized scheduler that has an end-to-end delay of approximately O(&#963;_i/&#961;_i + &#931; (l &#949; p_i) N / r_l), where r_l is the total rate of flows through link l, N is the number of links in the network, and p_i is the path followed by packets of flow i. We then show how to convert this into a distributed scheduler. We also study the extent to which results on the schedulability of packet deadlines can be carried over from the wireline to the wireless context. Lastly, we examine ways in which the theoretical schedulers considered in this paper can be transferred to a more practical random-access based setting. This work was supported by NSF contract CCF-0728980 and was performed while the first author was visiting Bell Labs in Summer, 2009.

Transforming Distributed Acyclic Systems into Equivalent Uniprocessors under Preemptive and Non-Preemptive Scheduling

Many scientific disciplines provide composition primitives whereby overall properties of systems are composed from those of their components. Examples include rules for block diagram reduction in control theory and laws for computing equivalent circuit impedance in circuit theory. No general composition rules exist for real-time systems whereby a distributed system is transformed to an equivalent single stage analyzable using traditional uniprocessor schedulability analysis techniques. Towards such a theory, in this paper, we extend our previous result on pipeline delay composition for preemptive and non-preemptive scheduling to the general case of distributed acyclic systems. Acyclic systems are defined as those where the superposition of all task flows gives rise to a Directed Acyclic Graph (DAG). The new extended analysis provides a worst-case bound on the end-to-end delay of a job under both preemptive as well as non-preemptive scheduling, in the distributed system. A simple transformation is then shown of the distributed task system into an equivalent uniprocessor task-set analyzable using traditional uniprocessor schedulability analysis. Hence, using the transformation described in this paper, the wealth of theory available for uniprocessor schedulability analysis can be easily applied to a larger class of distributed systems.

Delay composition in preemptive and non-preemptive real-time pipelines

Uniprocessor schedulability theory made great strides, in part, due to the simplicity of composing the delay of a job from the execution times of higher-priority jobs that preempt it. In this paper, we bound the end-to-end delay of a job in a multistage pipeline as a function of job execution times on different stages under preemptive as well as non-preemptive scheduling. We show that the end-to-end delay is bounded by that of a single virtual “bottleneck” stage plus a small additive component. This contribution effectively transforms the pipeline into a single stage system. The wealth of schedulability analysis techniques derived for uniprocessors can then be applied to decide the schedulability of the pipeline. The transformation does not require imposing artificial per-stage deadlines, but rather models the pipeline as a whole and uses the end-to-end deadlines directly in the single-stage analysis. It also does not make assumptions on job arrival patterns or periodicity and thus can be applied to periodic and aperiodic tasks alike. We show through simulations that this approach outperforms previous pipeline schedulability tests except for very short pipelines or when deadlines are sufficiently large. The reason lies in the way we account for execution overlap among stages. We discuss how previous approaches account for overlap and point out interesting differences that lead to different performance advantages in different cases. Further, we also show that in certain cases non-preemptive scheduling can result in higher system utilization than preemptive scheduling in pipelined systems. We hope that the pipeline delay composition rule, derived in this paper, may be a step towards a general schedulability analysis foundation for large distributed systems.

End-to-End Delay Analysis of Distributed Systems with Cycles in the Task Graph

A significant problem with no simple solutions in current real-time literature is analyzing the end-to-end schedulability of tasks in distributed systems with cycles in the task graph. Prior approaches including network calculus and holistic schedulability analysis work best for acyclic task flows. They involve iterative solutions or offer no solutions at all when flows are non-acyclic. This paper demonstrates the construction of the first generalized closed-form expression for schedulability analysis in distributed task systems with non-acyclic flows. The approach is a significant extension to our previous work on schedulability in Directed Acyclic Graphs. Our main result is a bound on end-to-end delay for a task in a distributed system with non-acyclic task flows. The delay bound allows one of several schedulability tests to be performed. Evaluation shows that the schedulability tests thus constructed are less pessimistic than prior approaches for large distributed systems.

Rapid adjustment and adoption to MIaaS clouds

Emerging Managed Infrastructure as a Service (MIaaS) clouds allow enterprises to outsource their IT infrastructure as well as their IT management needs. One of the core tenets of a MIaaS cloud is a standardized service delivery model, allowing the cloud provider to provide infrastructure management services at a lower cost. As opposed to pure IaaS clouds where arbitrary customer virtual machines can be migrated to the cloud, migration to MIaaS clouds require the customer servers to be adapted in a way such that the cloud steady state management stack can manage these virtual machines using the standardized delivery model. In this work, we address the problem of migrating customer workloads to a standardized MIaaS cloud. We present the design and implementation of Rapid Adjustment Engine (RAE). RAE captures the adjustment process across arbitrary customer servers with high diversity in a unified rule framework. It uses rapid image adjustment to reduce the end-to-end migration time and a flexible orchestrator framework to integrate diverse functionalities and associated tools in a single migration process. Our experimental evaluation establishes the ability of RAE to enable rapid, reliable and reduced cost migration to MIaaS clouds.