ABSTRACT

In recent years the labels “gossip ” and “gossip-based ” have been applied to an increasingly general class of algorithms, including approaches to information aggregation, overlay network management and clock synchronization. These algorithms are intuitively similar, irrespective of their purpose. Their distinctive features include relying on local information, being round-based and relatively simple, and having a bounded information transmission and processing complexity in each round. Our position is that this class can and should be significantly extended to involve algorithms from other disciplines that share the same or similar distinctive features, like certain parallel numerical algorithms, routing protocols, bio-inspired algorithms and cellular automata, to name but a few. Such a broader perspective would allow us to import knowledge and tools to design and understand gossip-based distributed systems, and we could also export accumulated knowledge to re-interpret some of the problems in other disciplines, such as vehicular traffic control. In this position paper we describe a number of areas that show parallels with gossip protocols. These example areas will hopefully serve as inspiration for future research. In addition, we believe that comparisons with other fields also helps clarify the definition of gossip protocols and represents a necessary first step towards an eventual formal definition. 1

Secure gossiping techniques and components

Gossip protocols have proved to be a viable solution to set-up and manage largescale P2P services or applications in a fully decentralised scenario. The gossip or epidemic communication scheme is heavily based on stochastic behaviors and it is the fundamental idea behind many large-scale P2P protocols. It provides many remarkable features, such as scalability, robustness to failures, emergent load balancing capabilities, fast spreading, and redundancy of information. In some sense, these services or protocols mimic natural system behaviors in order to achieve their goals. The key idea of this work is that the remarkable properties of gossip hold when all the participants follow the rules dictated by the actual protocols. If one or more malicious nodes join the network and start cheating according to some strategy, the result can be catastrophic. In order to study how serious the threat posed by malicious nodes can be and what can be done to prevent attackers from cheating, we focused on a general attack model aimed to defeat a key service in gossip overlay networks (the Peer Sampling Service [JGKvS04]). We also focused on the problem of protecting against forged information exchanged in gossip services. We propose a solution technique for each problem; both techniques are general enough to be applied to distinct service implementations. As gossip protocols, our solutions are based on stochastic behavior and are fully decentralized. In addition, each technique’s behaviour is abstracted by a general primitive function extending the basic gossip scheme; this approach allows the adoptions of our solutions with minimal changes in different scenarios. We provide an extensive experimental evaluation to support the effectiveness of our techniques. Basically, these techniques aim to be building blocks or P2P architecture guidelines in building more resilient and more secure P2P services

CoopNet: A Social, P2P-Like Simulation Model to Explore Knowledge-Based Production Processes

Aprevalent claim is that we are in a knowledge economy, where firms can be viewed as intra-organizational networks of knowledge nodes. Accordingly, firms\u2019 competitive advantage relies on their ability to support intellectual production processes that bridge talents and (possibly) foster durable work relations among employees in the organization. In this work, we propose a social, P2P-like simulation model, CoopNet, to investigate how intra organizational networking and organizational mechanisms interact to affect intra-organizational cooperation. More specifically, we examine how (a) different reward mechanisms and (b) alternative assumptions on workers\u2019 mobility within an intra-organizational network combine to influence cooperation. As a result, we highlight the role of (a) co-workers\u2019 selection and (b) continuity of working relationships as alternative mechanisms to foster cooperation within intra-organizational networks

Heuristic Driven Agents in Tax Evasion: An Agent-Based Approach

The Allingham and Sandmo model is an adaptation of the standard expected utility maximization framework where the taxpayer is defined as a representative agent who is coping with a risky choice. The main limit of this model regards the assumption of perfect rationality from the agent's side and the impossibility to study at the macro level a situation where many heterogeneous agents interact together. The aim of this work is to try to overcome, at least partially, some of the neoclassical standard approaches in this field. More precisely, we present a very simplified, agent-based, fiscal system with heterogeneous tax payers, interacting within a public good game framework. Heterogeneity has been introduced in our model by designing the agents like simple heuristics. The environment has been designed by a voluntary supply public good context reinforced through tax audits and fines. Looking for more realism, we also allowed agents to mutate their heuristics and we introduced two cross sectional types of agents: the "employees" and the "self-employees" allowing our agents to switch from one type to the other and vice-versa. Finally, the system is dynamic over time, since new agents can join over time to mimic the idea of having a growing population over time. We obtained is a complex adaptive system (CAS) with heterogeneous agents, dynamically evolving, able to describe the adaptation of agent's behaviour either concerning evading decision and the preferred kind of heuristic