Abstract Information extracted from social media has proven to be very useful in the domain of emergency management. An important task in emergency management is rapid crisis mapping, which aims to produce timely and reliable maps of affected areas. During an emergency, the volume of emergency-related posts is typically large, but only a small fraction is relevant and help rapid mapping effectively. Furthermore, posts are not useful for mapping purposes unless they are correctly geolocated and, on average, less than 2% of posts are natively georeferenced. This paper presents an algorithm, called CIME, that aims to identify and geolocate emergency-related posts that are relevant for mapping purposes. While native geocoordinates are most often missing, many posts contain geographical references in their metadata, such as texts or links that can be used by CIME to filter and geolocate information. In addition, social media creates a social network and each post can be enhanced with indirect information from the post’s network of relationships with other posts (for example, a retweet can be associated with other geographical references which are useful to geolocate the original tweet). To exploit all this information, CIME uses the concept of context, defined as the information characterizing a post both directly (the post’s metadata) and indirectly (the post’s network of relationships). The algorithm was evaluated on a recent major emergency event demonstrating better performance with respect to the state of the art in terms of total number of geolocated posts, geolocation accuracy and relevance for rapid mapping.

Extracting useful information from social networks raises several challenges that still represent open research issues. In this paper we focus on the problem of extracting geolocated images from Tweets to support emergency response. A Tweet analysis process is discussed, focusing on the selection of posts, their geolocation based on their text content, and the subsequent analysis of the images linked by geolocated tweets. A prototype system has been built and tested on a case study based on the Tweets posted in the two days after the earthquake that occurred in Central Italy in August 2016. Results indicate that focusing on images linked by geolocated tweets represents a good criterion to identify useful information that can aid emergency response.

This paper starts from the observation that social networks follow a power-law degree distribution of nodes, with a few hub nodes and a long tail of peripheral nodes. While there exist consolidated approaches supporting the identification and characterization of hub nodes, research on the analysis of the multi-layered distribution of peripheral nodes is limited. In social media, hub nodes represent social influencers. However, the literature provides evidence of the multi-layered structure of influence networks, emphasizing the distinction between influencers and influence. The latter seems to spread following multi-hop paths across nodes in peripheral network layers. This paper proposes a visual approach to the graphical representation and exploration of peripheral layers and clusters to exploit underlying concept of k-shell decomposition analysis. The core concept of our approach is to partition the node set of a graph into hub and peripheral nodes. Then, a power-law based modified force-directed method is applied to clearly display local multi-layered neighbourhood clusters around hub nodes. Our approach is tested on a large sample of tweets from the tourism domain. Empirical results indicate that peripheral nodes have a greater probability of being retweeted and, thus, play a critical role in determining the influence of content. Our visualization technique helps us highlight peripheral nodes and, thus, seems an interesting tool to the visual analysis of social influence.

Current multicast routing algorithms for multiprocessor systems are based on the reservation of transmission resources and buffer space for messages before transmission. This strategy causes cyclic dependencies among messages and, in turn, deadlock situations. This paper proposes and evaluates the performance of a new multicast routing algorithm, called Deadlock-Free Multicast Routing (DFMR), which removes the root cause of deadlocks. DFMR prevents deadlocks by allowing nodes to send flits as soon as internode links are available for transmission. This is obtained by allowing any possible interleaving of flits from all messages on internode links. The resulting routing algorithm eliminates the need to implement deadlock avoidance, detection, and recovery mechanisms, but needs larger output buffers. In DFMR, message flits carry additional information overhead which is used to avoid deadlock. Simulation results show that this information overhead has a negligible impact on overall performance which is considerably greater than that of previous algorithms.

Application- and context-aware infrastructures involve the network in the execution of distributed applications through special devices, namely, theapplication cards, placed in network nodes. The sharp separation of applications and network is smoothed, and by performing part of the distributed application inside the network, it is possible to reduce costs and improve performance with a better optimization of the whole distributed information and communication technology (ICT) infrastructure. This optimization is allowed by the additional degrees of freedom of placing cards in nodes and of assigning applications to such cards. In this paper, we provide an optimization algorithm that minimizes the total cost of the entire distributed ICT infrastructure, given a target performance objective defined as the end-to-end delay for the completion of the distributed application tasks. We focus on two sample applications that are well suited for application- and context-aware infrastructures:cachingandprotocol translation. The joint optimization of computing and communication resources is an innovative contribution of this paper, as, in the literature, hardware and network components are typically optimized separately. Results show that the total infrastructural cost savings are in the range of 15%-20%. However, savings can be obtained only if cards satisfy a cost-performance curve that is also analyzed.

The relationship among software design quality, development effort, and governance practices is a traditional research problem. However, the extent to which consolidated results on this relationship remain valid for open source (OS) projects is an open research problem. An emerging body of literature contrasts the view of open source as an alternative to proprietary software and explains that there exists a continuum between closed and open source projects. This paper hypothesizes that as projects approach the OS end of the continuum, governance becomes less formal. In turn a less formal governance is hypothesized to require a higher-quality code as a means to facilitate coordination among developers by making the structure of code explicit and facilitate quality by removing the pressure of deadlines from contributors. However, a less formal governance is also hypothesized to increase development effort due to a more cumbersome coordination overhead. The verification of research hypotheses is based on empirical data from a sample of 75 major OS projects. Empirical evidence supports our hypotheses and suggests that software quality, mainly measured as coupling and inheritance, does not increase development effort, but represents an important managerial variable to implement the more open governance approach that characterizes OS projects which, in turn, increases development effort.

Multiple combinations of hardware and network components can be selected to design an information technology (IT) infrastructure that satisfies requirements. The professional criterion to deal with these degrees of freedom is cost minimization. However, a scientific approach has been rarely applied to cost minimization, particularly for the joint optimization of hardware and network systems. This paper provides an overall methodology for combining hardware and network designs in a single cost minimization problem for multisite computer systems. Costs are minimized by applying a heuristic optimization approach to a sound decomposition of the problem. We consider most of the design alternatives that are enabled by current hardware and network technologies, including server sizing, localization of mutitier applications, and reuse of legacy systems. The methodology is empirically verified with a database of costs that has also been built as part of this paper. Verifications consider several test cases with different computing and communication requirements. Cost reductions are evaluated by comparing the cost of methodological results with those of architectural solutions that are obtained by applying professional design guidelines. The quality of heuristic optimization results is evaluated through comparison with lower bounds.

A quality degradation effect of proprietary code has been observed as a consequence of maintenance. This quality degradation effect, called entropy, is a cause for higher maintenance costs. In the Open Source context, the quality of code is a fundamental tenet of open software developers. As a consequence, the quality degradation principle measured by entropy cannot be assumed to be valid. The goal of the paper is to analyze the entropy of Open Source applications by measuring the evolution of maintenance costs over time. Analyses are based on cost data collected from a sample of 1251 Open Source application versions, compared with the costs estimated with a traditional model for proprietary software. Findings indicate that Open Source applications are less subject to entropy, have lower maintenance costs and also a lower need for maintenance interventions aimed at restoring quality. Finally, results show that a lower entropy is favored by greater functional simplicity.

This paper proposes a routing algorithm for the interconnection of multiple processors based on the shortest-path and deflection-routing principles. The routing algorithm, named SPDRA (Shortest Path and Deflection Routing Algorithm), is applied to multiprocessor systems with a single-stage shuffle physical topology. SPDRA is general-purpose, as opposed to the majority of routing algorithms for multiprocessor systems which are optimized for particular traffic patterns generated by a restricted class of parallel algorithms. The general-purpose nature of SPDRA allows perfomance comparisons with a wide class of routing algorithms for multiprocessor systems that, similar to the single-stage shuffle physical topology, have a fixed node-to-processor ratio. The paper compares SPDRA with hypercube algorithms for bidimensional meshes and torus physical topologies, routing algorithms for hierarchical tridimensional tori, and algorithms for routing permutations in shuffle networks, which constitute the most widely accepted approaches for multiprocessor interconnection. SPDRA exhibits a performance advantage for a broad range of network sizes and, in general, the performance advantage grows as the number of processors increases. However, this paper compares the SPDRA algorithm against a limited set of multiprocessor systems and does not demonstrate a general superiority of SPDRA over all systems with a fixed node-to-processor ratio and, especially, with a growing node-to-processor ratio, such as multistage networks.

The paper faces the problem of the runtime negotiation on the traffic conditioning agreement (TCA) and service level agreement (SLA) in IP differentiated services (DiffServ) networks. A first contribution of the paper with respect to previous literature is to propose a multi-attribute description of QoS targets and traffic profile. A second contribution of this work is to provide a mathematical formalization of the negotiation problem suitable for automated negotiation. The model is tested through simulation to a) verify the convergence of the negotiation process, which is critical to ensure that negotiation can be performed automatically and b) analyze the agreement solutions that are reached by negotiation parties for different values of quality of service and price parameters. Results show that the model has a sound convergence. With this paper's negotiation model, the primary goal of negotiating parties is to maintain the value of their utility function constant by searching a trade-off between QoS and price. However, the willingness to cooperate of the negotiating parties has a strong impact on the agreement value of negotiation parameters.

In a cooperative context, negotiation represents the process that allows organizations to create a base of common knowledge. Organizations have at the same time shared and divergent objectives and, thus, negotiating the characteristics of a common knowledge base cannot be fully cooperative, but inevitably raises competitive behaviours. The coopetition paradigm has been introduced in the literature to model relationships between companies that are simultaneously cooperative and competitive. The academic research has proposed several solutions for automated negotiation. A common characteristic of the protocols and algorithms that have been previously proposed is that they study negotiation only from a transactional and competitive point of view. This paper provides a model of the coopetitive negotiation process leading to underwriting a business insurance policy. Negotiation is modeled as an iterative question and answer process through which the parties create a common knowledge base of client's requirements and supplier's quality of service. This common knowledge defines the characteristics of the insurance policy and, hence, of the cooperative process that will follow the underwriting of the policy. The model has been implemented as an agent-based negotiation environment and analyzed through simulation.

E-services can be used to wrap an organization's information system and to provide a standard interface that enables cooperation with other information systems. As a consequence, e-services should not only support operating activities, but also embed mechanisms for inter-organizational coordination and control over operating activities. Inter-organizational coordination and control are based on contractual agreements that coordinate processes across cooperating companies and establish mechanisms to control the fulfillment of production goals. The objective of this paper is to describe a methodological approach for the design of e-services that supports the specification of inter-organizational coordination and control requirements. The paper explains how the methodology is structured in three phases, from requirements specification to conceptual design and implementation. The first phase of the methodology supports the specification of cooperation requirements, which constitute the static description of coordination and control requirements. In the second methodological phase, this static description is completed with a dynamic description of the actions to be taken upon exceptions, which occur when cooperating partners do not comply with cooperation goals. The static and dynamic description of coordination and control represent a conceptual specification of a business transaction. In the final methodological phase, this conceptual specification is implemented based on the WSDL and BPEL4WS languages for e-service design. The methodology is tested on the case study of the Italian production district of Matera.