Abstract
The ability of NoSQL systems to scale better than traditional relational databases motivates a large set of applications to migrate their data to NoSQL systems, even without aiming to exploit the provided schema exibility. However, accessing structured data is costly due to such exibility, incurring in a lot of bandwidth and processing unit usage. In this paper, we analyse this cost in Apache HBase and propose a new scan operation, named Prepared Scan, that optimizes the access to data structured in a regular manner by taking advantage of a well-known schema by application. Using an industry standard benchmark, we show that Prepared Scan improves throughput up to 29% and decreases network bandwidth consumption up to 20%. © 2017 ACM.

Abstract

Abstract
This paper briefly proposes a technique to detect energy inefficient fragments in the source code of a software system. Test cases are executed to obtain energy consumption measurements, and a statistical method, based on spectrum-based fault localization, is introduced to relate energy consumption to the system's source code. The result of our technique is an energy ranking of source code fragments pointing developers to possible energy leaks in their code.

Abstract
The paper explores the improvement in ancillary services that variable speed technologies can provide for the case of an existing pumped storage power plant of 2x210 MVA which conversion from fixed speed to variable speed is investigated with a focus on the power step performances of the units. First two motor-generator variable speed technologies are introduced, namely the Doubly Fed Induction Machine (DFIM) and the Full Scale Frequency Converter (FSFC). Then a detailed numerical simulation model of the investigated power plant used to simulate power steps response and comprising the waterways, the pump-turbine unit, the motor-generator, the grid connection and the control systems is presented. Hydroelectric system time domain simulations are performed in order to determine the shortest response time achievable, taking into account the constraints from the maximum penstock pressure and from the rotational speed limits. It is shown that the maximum instantaneous power step response up and down depends on the hydro-mechanical characteristics of the pump-turbine unit and of the motor-generator speed limits. As a results, for the investigated test case, the FSFC solution offer the best power step response performances.

Abstract
The original version of this article unfortunately contained amistake. The presentation of Table 3 was incorrect. The corrected (Table 3) is given below. © 2017, Springer Science+Business Media New York.

Abstract
With an advancement towards the paradigm of Internet of Things (IoT), in which every device will be interconnected and communicating with each other, the field of wireless sensor networks has helped to resolve an ever-growing demand in meeting deadlines and reducing power consumption. Among several standards that provide support for IoT, the recently published IEEE 802.15.4e protocol is specifically designed to meet the QoS requirements of industrial applications. IEEE 802.15.4e provides five Medium-Access Control (MAC) behaviors, including three that target time-critical applications: Deterministic and Synchronous Multichannel Extension (DSME); Time Slotted Channel Hopping (TSCH) and Low Latency Deterministic Network (LLDN). However, the standard and the literature do not provide any worst-case bound analysis of these behaviors, thus it is not possible to effectively predict their timing performance in an application and accurately devise a network in accordance to such constraints. This paper fills this gap by contributing network models for the three time-critical MAC behaviors using Network Calculus. These models allow deriving the worst-case performance of the MAC behaviors in terms of delay and buffering requirements. We then complement these results by carrying out a thorough performance analysis of these MAC behaviors by observing the impact of different parameters. © 2017 IEEE.