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Congestion control protocols for background data are commonly conceived and designed to emulate low priority traffic, which yields to transmission control protocol (TCP) flows. In the presence of even a few very long TCP flows, this behavior can cause bandwidth starvation, and hence, the accumulation of large numbers of background data flows for prolonged periods of time, which may ultimately have an adverse effect on the download delays of delay-sensitive TCP flows. In this paper, we look at the fundamental problem of designing congestion control protocols for background traffic with the minimum impact on short TCP flows while achieving a certain desired average throughput over time . The corresponding optimal policy under various assumptions on the available information is obtained analytically. We give tight bounds of the distance between TCP-based background transfer protocols and the optimal policy, and identify the range of system parameters for which more sophisticated congestion control makes a noticeable difference. Based on these results, we propose an access control algorithm for systems where control on aggregates of background flows can be exercised, as in file servers. Simulations of simple network topologies suggest that this type of access control performs better than protocols emulating low priority over a wide range of parameters.

We consider the problem of designing access control protocols for servers distributing background data, such as software and database updates, so that they cause the least possible disruption to flows carrying delay-sensitive data. Using a Markov decision process formulation we obtain the optimal policy analytically, which is not easy to implement in practice. A mean-field argument is employed to show that another policy, which is easier to implement and is based on water-filling, converges to the optimal as the number of bottleneck links increases. Using simulations we compare the performance of this policy with the standard case where no control is exercised by the server.

This paper aims to unravel the intricacies of the mechanisms of trust vis-i-vis ICTs and the contextual logic guiding user deployment and experience, necessitating a view of trust in the digital realm as a dynamic process. Trust models tend to highlight 'well-placed trust' in their focus on drawing out subcomponents of perceived trustworthiness as attributes of the trusted system or party from the trustor's stance. However, less attention has been given to the trustworthy attributes, or behavior of the trusted actor. Therefore, this paper sets out to explore this linkage between ICTs and different trust-related user experiences guided by different sets of trustor attributes. In order to explore the conceptual dynamics, a two-step approach is deployed. On the basis of empirical data attention is drawn to trust levels and user segments. Preliminary insights are yielded into the trustors' segmentation validity and trust estimation accuracy by performing a small-scale experiment in the context of a fictitious online security service.

Service providers face the ever-increasing problem of meeting customer expectations while maximizing profits. This optimal balance is very important for delivering better service quality to users and keeping costs under control through efficient resource allocation. In this paper we suggest optimal strategies for managing system trustworthiness in two different contexts. In the first one the provider has limited information about the users' trustworthiness preferences, which have to be satisfied on every transaction. In the second context, the provider knows what the effect of possible outcomes on customer's trust level and, given that the customer will perform a certain number of transactions, would like to know whether the system trustworthiness should be managed at any point in time in order to meet customer's expectations in a cost-effective way. The optimality of the proposed strategies is demonstrated via both analytical techniques and simulations.

In this article, we describe an approach for computing the current trust level of individual users towards an online system and present initial validation results from a small-scale experiment. This trust computational model relies upon survey research for identifying the set of key trust attributes and grouping users into four segments of expected behaviors. Each user’s initial trust level is computed based on a set of assumptions tailored to the specific segment she belongs to, while the trust level evolution takes additionally into account the system outcomes she has experienced so far. More specifically, the trust update follows a machine learning approach, where during the training phase that consists of a small number of system outcomes, users are asked to report their actual trust levels. Finally, we demonstrate the trustors’ segmentation validity and trust estimation accuracy by performing a small-scale experiment in the context of a fictitious online security service.

We consider the design of transport protocols for background transfers with the aim of reducing the download delays of interactive (non-background) flows which share the same links. We demonstrate that Lower than Best Effort (LBE) protocols suffer from bandwidth starvation, a fact which not only creates adoption disincentives but can have a harmful effect on the interactive flows as well. Instead we propose a simple access control policy which limits the maximum number of simultaneously transmitting background flows. This maximum limit is dynamically adjusted in order to prevent bandwidth starvation thus eliminating the disincentives present in LBE protocols. Through simulations we show that our policy creates lower transfer delay for the interactive flows, as compared to that under LEDBAT [6] and TCP-LP [8] LBE protocols.

Many, if not most, well-designed Future Internet protocols fail, and some badly-designed protocols are very successful. This somewhat depressing statement illustrates starkly the critical importance of a protocol's deployability. We present a framework for considering deployment and adoption issues, and apply it to two protocols, Multipath TCP and Congestion Exposure, which we are developing in the Trilogy project. Careful consideration of such issues can increase the chances that a future Internet protocol is widely adopted.

Networking research aims to design protocols for future Internet architectures that are able to hold end hosts accountable for the congestion they cause. Re-ECN is a protocol that provides valuable information to ISPs about network congestion, and which could be used as a useful input to support the allocation of network resources more equitably. In this paper, we propose and apply an adoption framework for the re-ECN protocol. As well as the technical design aspects, we also focus on the high level challenges and opportunities for the key stakeholders and present potential deployment scenarios that might lead to the widespread adoption of re-ECN.