BitWorker, a Decentralized Distributed Computing System based on BitTorrent

In this paper we present BitWorker, a platform for community distributed computing based on BitTorrent. Any splittable task can be easily specified by a user in a meta-information task file, such that it can be downloaded and performed by other volunteers. Peers find each other using Distributed Hash Tables, download existing results, and compute missing ones. Unlike existing distributed computing schemes relying on centralized coordination point(s), our scheme is totally distributed, therefore, highly robust. We evaluate the performance of BitWorker using mathematical models and real tests, showing processing and robustness gains. BitWorker is available for download and use by the community.

Resistive-Polymer Versus Forced-Air Warming: Comparable Efficacy in Orthopedic Patients

BACKGROUND: Several adverse consequences are caused by mild perioperative hypothermia. Maintaining normothermia with patient warming systems, today mostly with forced air (FA), has thus become a standard procedure during anesthesia. Recently, a polymer-based resistive patient warming system was developed. We compared the efficacy of a widely distributed FA system with the resistive-polymer (RP) system in a prospective, randomized clinical study. METHODS: Eighty patients scheduled for orthopedic surgery were randomized to either FA warming (Bair Hugger warming blanket #522 and blower #750, Arizant, Eden Prairie, MN) or RP warming (Hot Dog Multi-Position Blanket and Hot Dog controller, Augustine Biomedical, Eden Prairie, MN). Core temperature, skin temperature (head, upper and lower arm, chest, abdomen, back, thigh, and calf), and room temperature (general and near the patient) were recorded continuously. RESULTS: After an initial decrease, core temperatures increased in both groups at comparable rates (FA: 0.33 degrees C/h +/- 0.34 degrees C/h; RP: 0.29 degrees C/h +/- 0.35 degrees C/h; P = 0.6). There was also no difference in the course of mean skin and mean body (core) temperature. FA warming increased the environment close to the patient (the workplace of anesthesiologists and surgeons) more than RP warming (24.4 degrees C +/- 5.2 degrees C for FA vs 22.6 degrees C +/- 1.9 degrees C for RP at 30 minutes; P(AUC) <0.01). CONCLUSION: RP warming performed as efficiently as FA warming in patients undergoing orthopedic surgery.

[How the bovine viral diarrhea virus outwits the immune system]

The interaction of bovine viral diarrhea virus (BVD virus) with its host has several unique features, most notably the capacity to infect its host either transiently or persistently. The transient infection stimulates an antiviral immune reaction similar to that seen in other transient viral infections. In contrast, being associated with immunotolerance specific for the infecting BVD viral strain, the persistent infection differs fundamentally from other persistent infections like those caused by lentiviruses. Whereas the latter are characterized by complex viral evasion of the host's adaptive immune response by mechanisms such as antigenic drift and interference with presentation of T cell epitopes, BVD virus avoids the immune response altogether by inducing both humoral and cellular immune tolerance. This is made possible by invasion of the fetus at an early stage of development. In addition to adaptive immunity, BVD virus also manipulates key elements of the host's innate immune response. The non-cytopathic biotype of BVD virus, which is capable of persistently infecting its host, fails to induce type I interferon. In addition, persistently infected cells are resistant to the induction of apoptosis by double-stranded RNA and do not produce interferon when treated with this pathogen-associated molecular pattern (PAMP) that signals viral infection. Moreover, when treated with interferon, cells persistently infected with non-cytopathic BVD virus do not clear the virus. Surprisingly, however, despite this lack of effect on persistent infection, interferon readily induces an antiviral state in these cells, as shown by the protection against infection by unrelated viruses. Overall, BVD virus manipulates the host's interferon defense in a manner that optimises its chances of maintaining the persistent infection as well as decreasing the risks that heterologous viral infections may carry for the host. Thus, since not all potential host cells are infected in animals persistently infected with BVD virus, heterologous viruses replicating in cells uninfected with BVD virus will still trigger production of interferon. Interferon produced by such cells will curtail the replication of heterologous viruses only, be that in cells already infected with BVD virus, or in cells in which the heterologous virus may replicate alone. From an evolutionary viewpoint, this strategy clearly enhances the chances of transmission of BVD virus to new hosts, as it attenuates the negative effects that a global immunosuppression would have on the survival of persistently infected animals.

Connectionism as metaphor: Towards an integrated, unified conception of self-system and individual difference

Comments on an article by Kashima et al. (see record 2007-10111-001). In their target article Kashima and colleagues try to show how a connectionist model conceptualization of the self is best suited to capture the self's temporal and socio-culturally contextualized nature. They propose a new model and to support this model, the authors conduct computer simulations of psychological phenomena whose importance for the self has long been clear, even if not formally modeled, such as imitation, and learning of sequence and narrative. As explicated when we advocated connectionist models as a metaphor for self in Mischel and Morf (2003), we fully endorse the utility of such a metaphor, as these models have some of the processing characteristics necessary for capturing key aspects and functions of a dynamic cognitive-affective self-system. As elaborated in that chapter, we see as their principal strength that connectionist models can take account of multiple simultaneous processes without invoking a single central control. All outputs reflect a distributed pattern of activation across a large number of simple processing units, the nature of which depends on (and changes with) the connection weights between the links and the satisfaction of mutual constraints across these links (Rummelhart & McClelland, 1986). This allows a simple account for why certain input features will at times predominate, while others take over on other occasions. (PsycINFO Database Record (c) 2008 APA, all rights reserved)

Improving Management of Distributed Services Using Correlations and Predictions in SLA-Driven Cloud Computing Systems

Recent advancements in cloud computing have enabled the proliferation of distributed applications, which require management and control of multiple services. However, without an efficient mechanism for scaling services in response to changing environmental conditions and number of users, application performance might suffer, leading to Service Level Agreement (SLA) violations and inefficient use of hardware resources. We introduce a system for controlling the complexity of scaling applications composed of multiple services using mechanisms based on fulfillment of SLAs. We present how service monitoring information can be used in conjunction with service level objectives, predictions, and correlations between performance indicators for optimizing the allocation of services belonging to distributed applications. We validate our models using experiments and simulations involving a distributed enterprise information system. We show how discovering correlations between application performance indicators can be used as a basis for creating refined service level objectives, which can then be used for scaling the application and improving the overall application's performance under similar conditions.

SLA-driven predictive orchestration for distributed cloud-based mobile services

We describe a system for performing SLA-driven management and orchestration of distributed infrastructures composed of services supporting mobile computing use cases. In particular, we focus on a Follow-Me Cloud scenario in which we consider mobile users accessing cloud-enable services. We combine a SLA-driven approach to infrastructure optimization, with forecast-based performance degradation preventive actions and pattern detection for supporting mobile cloud infrastructure management. We present our system's information model and architecture including the algorithmic support and the proposed scenarios for system evaluation.

User and Machine Authentication and Authorization Infrastructure for Distributed Wireless Sensor Network Testbeds

The intention of an authentication and authorization infrastructure (AAI) is to simplify and unify access to different web resources. With a single login, a user can access web applications at multiple organizations. The Shibboleth authentication and authorization infrastructure is a standards-based, open source software package for web single sign-on (SSO) across or within organizational boundaries. It allows service providers to make fine-grained authorization decisions for individual access of protected online resources. The Shibboleth system is a widely used AAI, but only supports protection of browser-based web resources. We have implemented a Shibboleth AAI extension to protect web services using Simple Object Access Protocol (SOAP). Besides user authentication for browser-based web resources, this extension also provides user and machine authentication for web service-based resources. Although implemented for a Shibboleth AAI, the architecture can be easily adapted to other AAIs.

Distributed Rate Allocation in Inter-Session Network Coding

In this work, we propose a distributed rate allocation algorithm that minimizes the average decoding delay for multimedia clients in inter-session network coding systems. We consider a scenario where the users are organized in a mesh network and each user requests the content of one of the available sources. We propose a novel distributed algorithm where network users determine the coding operations and the packet rates to be requested from the parent nodes, such that the decoding delay is minimized for all clients. A rate allocation problem is solved by every user, which seeks the rates that minimize the average decoding delay for its children and for itself. Since this optimization problem is a priori non-convex, we introduce the concept of equivalent packet flows, which permits to estimate the expected number of packets that every user needs to collect for decoding. We then decompose our original rate allocation problem into a set of convex subproblems, which are eventually combined to obtain an effective approximate solution to the delay minimization problem. The results demonstrate that the proposed scheme eliminates the bottlenecks and reduces the decoding delay experienced by users with limited bandwidth resources. We validate the performance of our distributed rate allocation algorithm in different video streaming scenarios using the NS-3 network simulator. We show that our system is able to take benefit of inter-session network coding for simultaneous delivery of video sessions in networks with path diversity.

SLA-Driven Simulation of Multi-Tenant Scalable Cloud-Distributed Enterprise Information Systems

Cloud Computing is an enabler for delivering large-scale, distributed enterprise applications with strict requirements in terms of performance. It is often the case that such applications have complex scaling and Service Level Agreement (SLA) management requirements. In this paper we present a simulation approach for validating and comparing SLA-aware scaling policies using the CloudSim simulator, using data from an actual Distributed Enterprise Information System (dEIS). We extend CloudSim with concurrent and multi-tenant task simulation capabilities. We then show how different scaling policies can be used for simulating multiple dEIS applications. We present multiple experiments depicting the impact of VM scaling on both datacenter energy consumption and dEIS performance indicators.

A web-based non-intrusive ambient system to measure and classify activities of daily living.

BACKGROUND The number of older adults in the global population is increasing. This demographic shift leads to an increasing prevalence of age-associated disorders, such as Alzheimer's disease and other types of dementia. With the progression of the disease, the risk for institutional care increases, which contrasts with the desire of most patients to stay in their home environment. Despite doctors' and caregivers' awareness of the patient's cognitive status, they are often uncertain about its consequences on activities of daily living (ADL). To provide effective care, they need to know how patients cope with ADL, in particular, the estimation of risks associated with the cognitive decline. The occurrence, performance, and duration of different ADL are important indicators of functional ability. The patient's ability to cope with these activities is traditionally assessed with questionnaires, which has disadvantages (eg, lack of reliability and sensitivity). Several groups have proposed sensor-based systems to recognize and quantify these activities in the patient's home. Combined with Web technology, these systems can inform caregivers about their patients in real-time (e.g., via smartphone). OBJECTIVE We hypothesize that a non-intrusive system, which does not use body-mounted sensors, video-based imaging, and microphone recordings would be better suited for use in dementia patients. Since it does not require patient's attention and compliance, such a system might be well accepted by patients. We present a passive, Web-based, non-intrusive, assistive technology system that recognizes and classifies ADL. METHODS The components of this novel assistive technology system were wireless sensors distributed in every room of the participant's home and a central computer unit (CCU). The environmental data were acquired for 20 days (per participant) and then stored and processed on the CCU. In consultation with medical experts, eight ADL were classified. RESULTS In this study, 10 healthy participants (6 women, 4 men; mean age 48.8 years; SD 20.0 years; age range 28-79 years) were included. For explorative purposes, one female Alzheimer patient (Montreal Cognitive Assessment score=23, Timed Up and Go=19.8 seconds, Trail Making Test A=84.3 seconds, Trail Making Test B=146 seconds) was measured in parallel with the healthy subjects. In total, 1317 ADL were performed by the participants, 1211 ADL were classified correctly, and 106 ADL were missed. This led to an overall sensitivity of 91.27% and a specificity of 92.52%. Each subject performed an average of 134.8 ADL (SD 75). CONCLUSIONS The non-intrusive wireless sensor system can acquire environmental data essential for the classification of activities of daily living. By analyzing retrieved data, it is possible to distinguish and assign data patterns to subjects' specific activities and to identify eight different activities in daily living. The Web-based technology allows the system to improve care and provides valuable information about the patient in real-time.

Simulation of SLA-based VM-scaling algorithms for cloud-distributed applications

Cloud Computing has evolved to become an enabler for delivering access to large scale distributed applications running on managed network-connected computing systems. This makes possible hosting Distributed Enterprise Information Systems (dEISs) in cloud environments, while enforcing strict performance and quality of service requirements, defined using Service Level Agreements (SLAs). {SLAs} define the performance boundaries of distributed applications, and are enforced by a cloud management system (CMS) dynamically allocating the available computing resources to the cloud services. We present two novel VM-scaling algorithms focused on dEIS systems, which optimally detect most appropriate scaling conditions using performance-models of distributed applications derived from constant-workload benchmarks, together with SLA-specified performance constraints. We simulate the VM-scaling algorithms in a cloud simulator and compare against trace-based performance models of dEISs. We compare a total of three SLA-based VM-scaling algorithms (one using prediction mechanisms) based on a real-world application scenario involving a large variable number of users. Our results show that it is beneficial to use autoregressive predictive SLA-driven scaling algorithms in cloud management systems for guaranteeing performance invariants of distributed cloud applications, as opposed to using only reactive SLA-based VM-scaling algorithms.

The interplay between host genetic variation, viral replication and microbial translocation in untreated HIV-infected individuals.

Systemic immune activation, a major determinant of HIV disease progression, is the result of a complex interplay between viral replication, dysregulation of the immune system, and microbial translocation due to gut mucosal damage. While human genetic variants influencing HIV viral load have been identified, it is unknown to what extent the host genetic background contributes to inter-individual differences in other determinants of HIV pathogenesis like gut damage and microbial translocation. Using samples and data from 717 untreated participants in the Swiss HIV Cohort Study and a genome-wide association study design, we searched for human genetic determinants of plasma levels of intestinal fatty-acid binding protein (I-FABP/FABP2), a marker of gut damage, and of soluble sCD14 (sCD14), a marker of LPS bioactivity and microbial translocation. We also assessed the correlations between HIV viral load, sCD14 and I-FABP. While we found no genome-wide significant determinant of the tested plasma markers, we observed strong associations between sCD14 and both HIV viral load and I-FABP, shedding new light on the relationships between processes that drive progression of untreated HIV infection.

Service Level Agreements-Driven Management of Distributed Applications in Cloud Computing Environments

Cloud Computing enables provisioning and distribution of highly scalable services in a reliable, on-demand and sustainable manner. However, objectives of managing enterprise distributed applications in cloud environments under Service Level Agreement (SLA) constraints lead to challenges for maintaining optimal resource control. Furthermore, conflicting objectives in management of cloud infrastructure and distributed applications might lead to violations of SLAs and inefficient use of hardware and software resources. This dissertation focusses on how SLAs can be used as an input to the cloud management system, increasing the efficiency of allocating resources, as well as that of infrastructure scaling. First, we present an extended SLA semantic model for modelling complex service-dependencies in distributed applications, and for enabling automated cloud infrastructure management operations. Second, we describe a multi-objective VM allocation algorithm for optimised resource allocation in infrastructure clouds. Third, we describe a method of discovering relations between the performance indicators of services belonging to distributed applications and then using these relations for building scaling rules that a CMS can use for automated management of VMs. Fourth, we introduce two novel VM-scaling algorithms, which optimally scale systems composed of VMs, based on given SLA performance constraints. All presented research works were implemented and tested using enterprise distributed applications.

A naturally occurring prfA truncation in a Listeria monocytogenes field strain contributes to reduced replication and cell-to-cell spread

Listeria (L.) monocytogenes is an environmental bacterium that may become an intracellular pathogen upon ingestion to cause gastroenteritis, septicaemia, abortions, and/or fatal infections of the central nervous system. We here describe a L. monocytogenes field strain (JF5171) isolated from a bovine placenta in the context of abortion, which exhibited attenuation in bovine brain-slice cultures. The whole genome of strain JF5171 was sequenced, and the invasion, replication, and intercellular spread of JF5171 were further analyzed by quantification of colony forming units and immunofluorescence studies. Phospholipase and hemolysis activity of JF5171 were also quantified along with transcription levels of actA, hly and prfA. The data obtained were compared to those of the widely used L. monocytogenes reference strain, EGD-e. JF5171 exhibited reduced replication and lower levels of phospholipase and hemolysis activity. Invasion and cell-to-cell spread was strongly decreased compared to EGD-e, and actin polymerization was absent. A frame shift deletion was identified in the JF5171 coding region of the major regulator for virulence, prfA. This resulted in a truncated C-terminus sequence (WEN* vs. WGKLN*). In addition, a point mutation resulted in a lysine to arginine substitution at amino acid position 197. Complementation with prfA from EGD-e and with (EGD-e) prfA-K197N increased the replication and spread efficiency of JF5171. In contrast, complementation with the truncated version of prfA had no effect. Taken together, these results suggest that the truncated C-terminus of prfA considerably contributes to the strongly attenuated phenotype observed in vitro.

Positive and negative mutant selection in the human histone hairpin-binding protein using the yeast three-hybrid system.

We have used the yeast three-hybrid system in a positive selection for mutants of the human histone hairpin-binding protein (HBP) capable of interacting with non-canonical hairpins and in a negative selection for loss-of-binding mutants. Interestingly, all mutations from the positive selection are located in the N- and C-terminal regions flanking a minimal RNA-binding domain (RBD) previously defined between amino acids 126 and 198. Further, in vitro binding studies demonstrate that the RBD, which shows no obvious similarity to other RNA-binding motifs, has a relaxed sequence specificity compared to full-length HBP, allowing it to bind to mutant hairpin RNAs not normally found in histone genes. These findings indicate that the sequences flanking the RBD are important for restricting binding to the highly conserved histone hairpin structure. Among the loss-of-binding mutations, about half are nonsense mutations distributed throughout the N-terminal part and the RBD whereas the other half are missense mutations restricted to the RBD. Whereas the nonsense mutations permit a more precise definition of the C-terminal border of the RBD, the missense mutations identify critical residues for RNA binding within the RBD.