Spyros Sioutas

Integrating GIS, GPS and GSM technologies for the effective management of ambulances

In this paper, we describe a system offering a solution to the problem of ambulance management and emergency incident handling in the prefecture of Attica in Greece. It is based on the integration of geographic information system (GIS), global positioning system (GPS) and global system for mobile communication (GSM) technologies. The design of the system was the result of a project funded by the Greek Secretariat of Research and Technology. A significant operation for the handling of emergency incidents is the routing of ambulances to incident sites and then to the closest appropriate hospitals. The response time of a real-time system like ours to such queries is of vital significance. By using efficient data structures for the implementation of the graph representing the road network, the time performance of the shortest-path algorithm can be enhanced. Incorporating the efficient algorithm within the GIS will increase our systems viability.

Automated, Elastic Resource Provisioning for NoSQL Clusters Using TIRAMOLA

This work presents TIRAMOLA, a cloud-enabled, open-source framework to perform automatic resizing of NoSQL clusters according to user-defined policies. Decisions on adding or removing worker VMs from a cluster are modeled as a Markov Decision Process and taken in real-time. The system automatically decides on the most advantageous cluster size according to user-defined policies, it then proceeds on requesting/releasing VM resources from the provider and orchestrating them inside a NoSQL cluster. TIRAMOLAs modular architecture and standard API support allows interaction with most current IaaS platforms and increased customization. An extensive experimental evaluation on an HBase cluster confirms our assertions: The system resizes clusters in real-time and adapts its performance through different optimization strategies, different permissible actions, different input and training loads. Besides the automation of the process, it exhibits a learning feature which allows it to make very close to optimal decisions even with input loads 130% larger or alternating 10 times faster compared to the accumulated information.

Improved bounds for finger search on a ram

We present a new finger search tree with O(loglogd) expected search time in the Random Access Machine (RAM) model of computation for a large class of input distributions. The parameter d represents the number of elements (distance) between the search element and an element pointed to by a finger, in a finger search tree that stores n elements. Our data structure improves upon a previous result by Andersson and Mattsson that exhibits expected O(loglogn) search time by incorporating the distance d into the search time complexity, and thus removing the dependence on n. We are also able to show that the search time is O(loglogd+ϕ(n)) with high probability, where ϕ(n) is any slowly growing function of n. For the need of the analysis we model the updates by a “balls and bins” combinatorial game that is interesting in its own right as it involves insertions and deletions of balls according to an unknown distribution.

Dynamic Web Service discovery architecture based on a novel peer based overlay network

Service Oriented Computing and its most famous implementation technology Web Services (WS) are becoming an important enabler of networked business models. Discovery mechanisms are a critical factor to the overall utility of Web Services. So far, discovery mechanisms based on the UDDI standard rely on many centralized and area-specific directories, which poses information stress problems such as performance bottlenecks and fault tolerance. In this context, decentralized approaches based on Peer to Peer overlay networks have been proposed by many researchers as a solution. In this paper, we propose a new structured P2P overlay network infrastructure designed for Web Services Discovery. We present theoretical analysis backed up by experimental results, showing that the proposed solution outperforms popular decentralized infrastructures for web discovery, Chord (and some of its successors), BATON (and its successor) and Skip-Graphs.

TIRAMOLA: elastic nosql provisioning through a cloud management platform

NoSQL databases focus on analytical processing of large scale datasets, offering increased scalability over commodity hardware. One of their strongest features is elasticity, which allows for fairly portioned premiums and high-quality performance. Yet, the process of adaptive expansion and contraction of resources usually involves a lot of manual effort, often requiring the definition of the conditions for scaling up or down to be provided by the users. To date, there exists no open-source system for automatic resizing of NoSQL clusters. In this demonstration, we present TIRAMOLA, a modular, cloud-enabled framework for monitoring and adaptively resizing NoSQL clusters. Our system incorporates a decision-making module which allows for optimal cluster resize actions in order to maximize any quantifiable reward function provided together with life-long adaptation to workload or infrastructural changes. The audience will be able to initiate HBase clusters of various sizes and apply varying workloads through multiple YCSB clients. The attendees will be able to watch, in real-time, the system perform automatic VM additions and removals as well as how cluster performance metrics change relative to the optimization parameters of their choice.

Dependable Horizontal Scaling Based on Probabilistic Model Checking

The focus of this work is the on-demand resource provisioning in cloud computing, which is commonly referredto as cloud elasticity. Although a lot of effort has been invested in developing systems and mechanisms that enable elasticity, the elasticity decision policies tend to be designed without quantifying or guaranteeing the quality of their operation. We present an approach towards the development of more formalized and dependable elasticity policies. We make two distinct contributions. First, we propose an extensible approach to enforcing elasticity through the dynamic instantiation and online quantitative verification of Markov Decision Processes(MDP) using probabilistic model checking. Second, various concrete elasticity models and elasticity policies are studied. We evaluate the decision policies using traces from a realNoSQL database cluster under constantly evolving externalload. We reason about the behaviour of different modelling and elasticity policy options and we show that our proposal can improve upon the state-of-the-art in significantly decreasing under-provisioning while avoiding over-provisioning.

On-line consistent ranking on e-recruitment: seeking the truth behind a well-formed CV

In this work we present a novel approach for evaluating job applicants in online recruitment systems, using machine learning algorithms to solve the candidate ranking problem and performing semantic matching techniques. An application of our approach is implemented in the form of a prototype system, whose functionality is showcased and evaluated in a real-world recruitment scenario. The proposed system extracts a set of objective criteria from the applicants’ LinkedIn profile, and compares them semantically to the job’s prerequisites. It also infers their personality characteristics using linguistic analysis on their blog posts. Our system was found to perform consistently compared to human recruiters, thus it can be trusted for the automation of applicant ranking and personality mining.

PLBSD: a platform for proactive location-based service discovery

We introduce a platform for the rapid prototyping of proactive location-based service discovery, proactive location-based services are conceptualised along three broad categories: location-triggered services chain-triggered services, proximity-triggered services, and illustrated through a number of usage scenarios. We report on a workshop with designers and researchers in the area of location-based services that resulted in a set of initial requirements for the platform. We describe how the platform aims at addressing these requirements, and illustrate the implemented features through the development of a proactive location-based application.

A novel distributed P2P simulator architecture: D-P2P-sim

In this paper we introduce a novel distributed simulation environment with GUI for P2P simulations (D-P2P-Sim). The key aim is to provide the appropriate integrated set of tools in a single software solution to evaluate the performance of various protocols. The basic architecture of the distributed P2P simulator is based on a multi-threading, asynchronous, message passing and distributed environment with graphical user interface to facilitate ease of use by both researchers and programmers.

NBDT: an efficient P2P indexing scheme for web service discovery

In this paper, we propose a new infrastructure for web services discovery in P2P networks, the Nested Balanced Distributed Tree (NBDT). Peers that store web services information, such as data item descriptions, are efficiently located using a scalable and robust data indexing structure based on a NBDT. The key innovation is that the solution is based on a totally new infrastructure, which is not vulnerable to classic disadvantages. We present a theoretical analysis backed up by experimental results, which shows that the communication cost of query and update operations scale sublogarithmically in the worst case with the number of NBDT nodes, outperforming three of the most popular decentralised infrastructures: Chord (and some of its successors), BATON (and its successor) and Skip Graphs. Furthermore, we show that the network is robust to failures providing quality of web services requirements.