Flavio Lombardi

AntiCheetah: Trustworthy computing in an outsourced (cheating) environment

Abstract The increasing need for performing expensive computations has motivated outsourced computing, as in crowdsourced applications leveraging worker cloud nodes. However, these outsourced computing nodes can potentially misbehave or fail. Exploiting the redundancy of nodes can help guaranteeing correctness and availability of results. This entails that reliable distributed computing can be achieved at the expense of convenience. In this paper, we provide a solution for a generic class of problems that distribute a parallel computation over a set of nodes where trustworthiness of the outsourced computation is important. In particular, we discuss AntiCheetah , an approach modeling the assignment of input elements to cloud nodes as a multi-round system. AntiCheetah is resilient to node cheating, even in scenarios where smart cheaters return the same fake values. To this end, cost-efficient redundancy is used to detect and correct anomalies. Furthermore, we discuss the benefits and pitfalls of the proposed approach over different scenarios, especially with respect to cheaters’ behavior. Extensive experimental results are analyzed, showing the effectiveness and viability of our approach.

Towards a GPU Cloud: Benefits and Security Issues

Graphics processing unit (GPU)-based clouds are gaining momentum, and GPU computing resources are starting to be offered as a cloud service, either as parallel computing power or accessible as a part of a leased virtual machine (VM). For this reason, the GPU cloud is one of the most promising cloud evolutions. However, the present cloud offerings do not effectively exploit GPU computing resources, which could well improve the performance and security of distributed computing systems. In fact, heterogeneous many-core hardware and especially GPUs, offer a potentially massive increase in computing power. They are also very power efficient, enabling significant price/performance improvements over traditional central processing units (CPUs). Unfortunately, and more importantly, GPU clouds do not guarantee an adequate level of security with respect to access control and isolation. There is no effective control on how parallel code (a.k.a. kernels) is actually executed on a GPU. In fact, the present GPU device drivers are entirely based on proprietary code and are optimized for performance rather than security. As a result, GPU architectures and hardware (HW)/software (SW) implementations are not yet considered to be mature enough for a GPU cloud. In particular, the level of security offered by this novel approach has yet to be fully investigated, as there is a limited security-related research that specifically targets GPU architectures. This chapter describes how GPU-as-a-Service can be exposed to misuse and to potential denial of service (DoS) and information leakage. It also shows how GPUs can be used as a security and integrity monitoring tool by the cloud, for instance, to provide timely integrity checking of VM code and data, allowing scalable management of the security of complex cloud computing infrastructures. Some further relevant security concerns are discussed in this chapter, including GPU service availability, access transparency and control.

Transparent java threads migration protocol over peer2peer

The Java Virtual Machine computing model implements a multi-threading paradigm but its computing model does not define and does not verify the distribution paradigm of the threads over set of JVM instances. Without a distribution paradigm the Java Virtual Machine computing model cannot get any advantage from the theory of parallel Turing Machines. This work formally specifies and verifies the JVM computing model distribution paradigm. An intrinsic transparent thread distribution mechanism over many JVMs relying on different communication technology such as Peer to Peer is an important outcome of the presented solution. Other consequences, such as distributed JVM run-time location, aggregation and reachability, are achieved. Moreover the creation of Virtual Farms of JVMs for Multi-threading applications computing is made possible.

Processes for software development within the Public Administration

The availability of open standards and tools have made often convenient for Public Administrations to internalize software development activities. In order to establish a software factory, it is critical to define processes. While many process standards have been devised over time, in our opinion there exist fewer effective guidelines on how to tailor them to an organizations actual needs. This paper describes the experience we acquired and the lessons we learned through the years on process definition by managing a number of software development projects within CNR1 Central Administration. In particular, a software development process is described that we consider adequate for small-to-medium-sized software factories (frequent case for non-ICT organizations). “Inclusion criteria” are also suggested for the artefacts of each phase, in order to allow further process tailoring. Our process is then discussed against a set of case studies which represent the empirical basis of our tailoring work. We believe our experience can be of use for other similar contexts, particularly within the Public Administration.