An experimental study of client-side Spotify peering behaviour

Spotify is a popular music-streaming service which has seen widespread use across Europe. While Spotify’s server-side behaviour has previously been studied, little is known about the client-side behaviour. In this paper, we describe an experimental study where we collect packet headers for Spotify traffic over multiple 24-hour time frames at a client host. Two distinct types of behaviour are observed, when tracks are being downloaded, and when the client is only serving requests from other peers. We also note wide variation in connection lifetimes, as seen in other studies of peer-to-peer systems. These findings are relevant for improving Spotify itself, and for the designers of other hybrid peer-to-peer and server-based distribution architectures

Policy-based management for body-sensor networks

Accepted versio

Towards supporting interactions between self-managed cells

Accepted versio

Dynamic ontology mapping for interacting autonomous systems

With the emergence of mobile and ubiquitous computing environments, there is a requirement to enable collaborative applications between these environments. As many of these applications have been designed to operate in isolation, making them work together is often complicated by the semantic and ontological differences in the meta-data describing the data to be shared. Typical approaches to overcoming ontological differences require the presence of a third party administrator, an approach incompatible with autonomous systems. This paper presents an approach to automatic ontology mapping suitable for deployment in autonomous, interacting systems for a class of collaborative application. The approach facilitates the collaboration of application-level data collections by identifying areas of ontological conflict and using meta-data values associated with those collections to establish commonality. A music sharing application has been developed to facilitate the sharing of music between peers

Wide-area SMC interaction, implementation and emulation

The primary components in a Self Managed Cell (SMC) -- the event bus, the policy management service, and the discovery service -- are required regardless of the scale of the SMC. However, the behaviour of core services may necessarily be altered to suit the environment within which an SMC operates. This paper discusses the design of core services (primarily, the event bus and discovery service) in wide- area SMCs. Delay-tolerant networking between SMCs is also discussed, as is the implementation of core services leading to an emulated network of SMCs. As the basis for a 'healthmap' capable of representing patient data across a geographic region, the discussion on wide-area SMCs leads into cursory discussion of geographical imaging and visualisation systems

Self-managed cell: a middleware for managing body-sensor networks

Body sensor networks consisting of low-power on- body wireless sensors attached to mobile users will be used in the future to monitor the health and well being of patients in hospitals or at home. Such systems need to adapt autonomously to changes in context, user activity, device failure, and the availability or loss of services. To this end, we propose a policy- based architecture that uses the concept of a Self-Managed Cell (SMC) to integrate services, managed resources and a policy interpreter by means of an event bus. Policies permit the declarative specification of adaptation strategy for self- configuration and self-management. We present the design and implementation of the SMC and describe its potential use in a scenario for management of heart monitoring. Preliminary performance measurements are also presented and discussed

Policy-based management of body-sensor networks

Body sensor networks e.g., for health monitoring, consist of several low-power on-body wireless sensors, higher-level devices such as PDAs and possibly actuators such as drug delivery pumps. It is important that such networks can adapt autonomously to changing conditions such as failures, changes in context e.g., user activity, or changes in the clinical condition of patients. Potential reconfiguration actions include changing the monitoring thresholds on sensors, the analysis algorithms or the configuration of the network itself. This paper presents a policy-based approach for autonomous management of body-sensor networks using the concept of a SelfManaged Cell (SMC). Ponder2 is an implementation of this approach that permits the specification and enforcement of policies that facilitate management and adaptation of the response to changing conditions. A Tiny Policy Interpreter has also been developed in order to provide programmable decision-making capability for BSN nodes

AMUSE: Autonomic Management of Ubiquitous e-Health Systems

Future e-Health systems will consist of low-power on-body wireless sensors attached to mobile users that interact with an ubiquitous computing environment to monitor the health and well being of patients in hospitals or at home. Patients or health practitioners have very little technical computing expertise so these systems need to be self-configuring and selfmanaging with little or no user input. More importantly, they should adapt autonomously to changes resulting from user activity, device failure, and the addition or loss of services. We propose the Self-Managed Cell (SMC) as an architectural pattern for all such types of ubiquitous computing applications and use an e-Health application in which on-body sensors are used to monitor a patient living in their home as an exemplar. We describe the services comprising the SMC and discuss cross-SMC interactions as well as the composition of SMCs into larger structures. KEYWORDS: Autonomic computing, pervasive systems, self-configuration, policy-based managemen