Foundational Theory for Understanding Policy Routing Dynamics

In this paper we introduce a theory of policy routing dynamics based on fundamental axioms of routing update mechanisms. We develop a dynamic policy routing model (DPR) that extends the static formalism of the stable paths problem (introduced by Griffin et al.) with discrete synchronous time. DPR captures the propagation of path changes in any dynamic network irrespective of its time-varying topology. We introduce several novel structures such as causation chains, dispute fences and policy digraphs that model different aspects of routing dynamics and provide insight into how these dynamics manifest in a network. We exercise the practicality of the theoretical foundation provided by DPR with two fundamental problems: routing dynamics minimization and policy conflict detection. The dynamics minimization problem utilizes policy digraphs, that capture the dependencies in routing policies irrespective of underlying topology dynamics, to solve a graph optimization problem. This optimization problem explicitly minimizes the number of routing update messages in a dynamic network by optimally changing the path preferences of a minimal subset of nodes. The conflict detection problem, on the other hand, utilizes a theoretical result of DPR where the root cause of a causation cycle (i.e., cycle of routing update messages) can be precisely inferred as either a transient route flap or a dispute wheel (i.e., policy conflict). Using this result we develop SafetyPulse, a token-based distributed algorithm to detect policy conflicts in a dynamic network. SafetyPulse is privacy preserving, computationally efficient, and provably correct.

Principles of Safe Policy Routing Dynamics

We introduce the Dynamic Policy Routing (DPR) model that captures the propagation of route updates under arbitrary changes in topology or path preferences. DPR introduces the notion of causation chains where the route flap at one node causes a flap at the next node along the chain. Using DPR, we model the Gao-Rexford (economic) guidelines that guarantee the safety (i.e., convergence) of policy routing. We establish three principles of safe policy routing dynamics. The non-interference principle provides insight into which ASes can directly induce route changes in one another. The single cycle principle and the multi-tiered cycle principle provide insight into how cycles of routing updates can manifest in any network. We develop INTERFERENCEBEAT, a distributed algorithm that propagates a small token along causation chains to check adherence to these principles. To enhance the diagnosis power of INTERFERENCEBEAT, we model four violations of the Gao-Rexford guidelines (e.g., transiting between peers) and characterize the resulting dynamics.

An Adaptive Policy Management Approach to BGP Convergence

The Border Gateway Protocol (BGP) is the current inter-domain routing protocol used to exchange reachability information between Autonomous Systems (ASes) in the Internet. BGP supports policy-based routing which allows each AS to independently adopt a set of local policies that specify which routes it accepts and advertises from/to other networks, as well as which route it prefers when more than one route becomes available. However, independently chosen local policies may cause global conflicts, which result in protocol divergence. In this paper, we propose a new algorithm, called Adaptive Policy Management Scheme (APMS), to resolve policy conflicts in a distributed manner. Akin to distributed feedback control systems, each AS independently classifies the state of the network as either conflict-free or potentially-conflicting by observing its local history only (namely, route flaps). Based on the degree of measured conflicts (policy conflict-avoidance vs. -control mode), each AS dynamically adjusts its own path preferences—increasing its preference for observably stable paths over flapping paths. APMS also includes a mechanism to distinguish route flaps due to topology changes, so as not to confuse them with those due to policy conflicts. A correctness and convergence analysis of APMS based on the substability property of chosen paths is presented. Implementation in the SSF network simulator is performed, and simulation results for different performance metrics are presented. The metrics capture the dynamic performance (in terms of instantaneous throughput, delay, routing load, etc.) of APMS and other competing solutions, thus exposing the often neglected aspects of performance.

An Adaptive Management Approach to Resolving Policy Conflicts

The Border Gateway Protocol (BGP) is the current inter-domain routing protocol used to exchange reachability information between Autonomous Systems (ASes) in the Internet. BGP supports policy-based routing which allows each AS to independently define a set of local policies on which routes it accepts and advertises from/to other networks, as well as on which route it prefers when more than one route becomes available. However, independently chosen local policies may cause global conflicts, which result in protocol divergence. In this paper, we propose a new algorithm, called Adaptive Policy Management Scheme(APMS), to resolve policy conflicts in a distributed manner. Akin to distributed feedback control systems, each AS independently classifies the state of the network as either conflict-free or potentially conflicting by observing its local history only (namely, route flaps). Based on the degree of measured conflicts, each AS dynamically adjusts its own path preferences---increasing its preference for observably stable paths over flapping paths. APMS also includes a mechanism to distinguish route flaps due to topology changes, so as not to confuse them with those due to policy conflicts. A correctness and convergence analysis of APMS based on the sub-stability property of chosen paths is presented. Implementation in the SSF network simulator is performed, and simulation results for different performance metrics are presented. The metrics capture the dynamic performance (in terms of instantaneous throughput, delay, etc.) of APMS and other competing solutions, thus exposing the often neglected aspects of performance.

The ways in which new public management ideas impact upon the administrative culture of 'street-level' bureaucrats and professionals working within Irish social policy

The conventional meaning of culture is ‘widely shared and strongly held values’ of a particular group or society (Bradley and Parker, 2006: 89). Culture is not a rigid concept; it can be influenced or altered by new ideas or forces. This research examines the ways in which one set of ideas in particular, that is, those associated with New Public Management, have impacted upon the administrative culture of 'street-level' bureaucrats and professionals within Irish social policy. Lipsky (1980: 3) defined 'street-level' bureaucrats as ‘public service workers who interact directly with citizens in the course of their jobs, and who have substantial discretion in the execution of their work’. Utilising the Competing Values Framework (CVF) in the analysis of eighty three semi-structured interviews with 'street-level' bureaucrats and professionals, an evaluation is made as to the impact of NPM ideas on both visible and invisible aspects of administrative culture. Overall, the influence of NPM is confined to superficial aspects of administrative culture such as; increased flexibility in working hours and to some degree job contracts; increased time commitment; and a customer service focus. However, the extent of these changes varies depending on policy sector and occupational group. Aspects of consensual and hierarchical cultures remain firmly in place. These coincide with features of developmental and market cultures. Contrary to the view that members of hierarchical and consensual culture would pose resistance to change, this research clearly illustrates that a very large appetite for change exists in the attitudes of 'street-level' bureaucrats and professionals within Irish social policy, with many of them suggesting changes that correspond to NPM ideas. This study demonstrates the relevance of employing the CVF model as it is clear that administrative culture is very much a dynamic system of competing and co-existing cultures.

Typical delay determines waiting time on periodic-food schedules: Static and dynamic tests.

Pigeons and other animals soon learn to wait (pause) after food delivery on periodic-food schedules before resuming the food-rewarded response. Under most conditions the steady-state duration of the average waiting time, t, is a linear function of the typical interfood interval. We describe three experiments designed to explore the limits of this process. In all experiments, t was associated with one key color and the subsequent food delay, T, with another. In the first experiment, we compared the relation between t (waiting time) and T (food delay) under two conditions: when T was held constant, and when T was an inverse function of t. The pigeons could maximize the rate of food delivery under the first condition by setting t to a consistently short value; optimal behavior under the second condition required a linear relation with unit slope between t and T. Despite this difference in optimal policy, the pigeons in both cases showed the same linear relation, with slope less than one, between t and T. This result was confirmed in a second parametric experiment that added a third condition, in which T + t was held constant. Linear waiting appears to be an obligatory rule for pigeons. In a third experiment we arranged for a multiplicative relation between t and T (positive feedback), and produced either very short or very long waiting times as predicted by a quasi-dynamic model in which waiting time is strongly determined by the just-preceding food delay.

Designing Climate Mitigation Policy

This paper provides an exhaustive review of critical issues in the design of climate mitigation policy by pulling together key findings and controversies from diverse literatures on mitigation costs, damage valuation, policy instrument choice, technological innovation, and international climate policy. We begin with the broadest issue of how high assessments suggest the near and medium term price on greenhouse gases would need to be, both under cost-effective stabilization of global climate and under net benefit maximization or Pigouvian emissions pricing. The remainder of the paper focuses on the appropriate scope of regulation, issues in policy instrument choice, complementary technology policy, and international policy architectures.

The dynamic efficiency costs of common-pool resource exploitation

We conduct the first empirical investigation of common-pool resource users' dynamic and strategic behavior at the micro level using real-world data. Fishermen's strategies in a fully dynamic game account for latent resource dynamics and other players' actions, revealing the profit structure of the fishery. We compare the fishermen's actual and socially optimal exploitation paths under a time-specific vessel allocation policy and find a sizable dynamic externality. Individual fishermen respond to other users by exerting effort above the optimal level early in the season. Congestion is costly instantaneously but is beneficial in the long run because it partially offsets dynamic inefficiencies.

Flexible self-adjustment of task deployment in dynamic environments

This paper presents an investigation into dynamic self-adjustment of task deployment and other aspects of self-management, through the embedding of multiple policies. Non-dedicated loosely-coupled computing environments, such as clusters and grids are increasingly popular platforms for parallel processing. These abundant systems are highly dynamic environments in which many sources of variability affect the run-time efficiency of tasks. The dynamism is exacerbated by the incorporation of mobile devices and wireless communication. This paper proposes an adaptive strategy for the flexible run-time deployment of tasks; to continuously maintain efficiency despite the environmental variability. The strategy centres on policy-based scheduling which is informed by contextual and environmental inputs such as variance in the round-trip communication time between a client and its workers and the effective processing performance of each worker. A self-management framework has been implemented for evaluation purposes. The framework integrates several policy-controlled, adaptive services with the application code, enabling the run-time behaviour to be adapted to contextual and environmental conditions. Using this framework, an exemplar self-managing parallel application is implemented and used to investigate the extent of the benefits of the strategy

Policy-based techniques for self-managing parallel applications

This paper presents an empirical investigation of policy-based self-management techniques for parallel applications executing in loosely-coupled environments. The dynamic and heterogeneous nature of these environments is discussed and the special considerations for parallel applications are identified. An adaptive strategy for the run-time deployment of tasks of parallel applications is presented. The strategy is based on embedding numerous policies which are informed by contextual and environmental inputs. The policies govern various aspects of behaviour, enhancing flexibility so that the goals of efficiency and performance are achieved despite high levels of environmental variability. A prototype self-managing parallel application is used as a vehicle to explore the feasibility and benefits of the strategy. In particular, several aspects of stability are investigated. The implementation and behaviour of three policies are discussed and sample results examined.

Policy-driven self-management for an automotive middleware

This paper describes work towards the deployment of self-managing capabilities into an advanced middleware for automotive systems. The middleware will support a range of futuristic use-cases requiring context-awareness and dynamic system configuration. Several use-cases are described and their specific context-awareness requirements identified. The discussion is accompanied by a justification for the selection of policy-based computing as the autonomics technique to drive the self-management. The specific policy technology to be deployed is described briefly, with a focus on its specific features that are of direct relevance to the middleware project. A selected use-case is explored in depth to illustrate the extent of dynamic behaviour achievable in the proposed middleware architecture, which is composed of several policy-configured services. An early demonstration application which facilitates concept evaluation is presented and a sequence of typical device-discovery events is worked through

Towards policy-based self-configuration of embedded systems

This paper describes work towards the deployment of flexible self-management into real-time embedded systems. A challenging project which focuses specifically on the development of a dynamic, adaptive automotive middleware is described, and the specific self-management requirements of this project are discussed. These requirements have been identified through the refinement of a wide-ranging set of use cases requiring context-sensitive behaviours. A sample of these use-cases is presented to illustrate the extent of the demands for self-management. The strategy that has been adopted to achieve self-management, based on the use of policies is presented. The embedded and real-time nature of the target system brings the constraints that dynamic adaptation capabilities must not require changes to the run-time code (except during hot update of complete binary modules), adaptation decisions must have low latency, and because the target platforms are resource-constrained the self-management mechanism have low resource requirements (especially in terms of processing and memory). Policy-based computing is thus and ideal candidate for achieving the self-management because the policy itself is loaded at run-time and can be replaced or changed in the future in the same way that a data file is loaded. Policies represent a relatively low complexity and low risk means of achieving self-management, with low run-time costs. Policies can be stored internally in ROM (such as default policies) as well as externally to the system. The architecture of a designed-for-purpose powerful yet lightweight policy library is described. A suitable evaluation platform, supporting the whole life-cycle of feasibility analysis, concept evaluation, development, rigorous testing and behavioural validation has been devised and is described.

A versatile policy toolkit supporting run-time policy reconfiguration

This paper describes an autonomics development tool which serves as both a powerful and flexible policy-expression language and a policy-based framework that supports the integration and dynamic composition of several autonomic computing techniques including signal processing, automated trend analysis and utility functions. Each of these technologies has specific advantages and applicability to different types of dynamic adaptation. The AGILE platform enables seamless interoperability of the different technologies to each perform various aspects of self-management within a single application. Self-management behaviour is specified using the policy language semantics to bind the various technologies together as required. Since the policy semantics support run-time re-configuration, the self-management architecture is dynamically composable. The policy language and implementation library have integrated support for self-stabilising behaviour, enabling oscillation and other forms of instability to be handled at the policy level with very little effort on the part of the application developer. Example applications are presented to illustrate the integration of different autonomics techniques, and the achievement of dynamic composition.

Embedding dynamic behaviour into a self-configuring software system

This paper describes a methodology for embedding dynamic behaviour into software components. The implications and system architecture requirements to support this adaptivity are discussed. This work is part of a European Commission funded and industry supported project to produce a reconfigurable middleware for use in automotive systems. Such systems must be trustable against illegal internal behaviour and activity with external origins, additional devices for example. Policy-based computing is used here as an example of embedded logic. A key contribution of this work is the way in which static and dynamic aspects of the system are interfaced, such that the behaviour can be changed very flexibly (even during run-time), without modification, recompilation or redeployment of the embedded application code. An implementation of these concepts is presented, focussing on achieving trust in the use of dynamic behaviour.

Dynamic analysis of employment trajectories through the concept of fl exicurity

The paper presents a dynamic study of the Spanish labour market which tries to determine if it matches the characteristics of transitional labour markets from a fl exicurity approach. Employment trajectories of Spanish workers during the years 2007-2010 are studied using the Continuous Sample of Working Lives. This period covers the end of the expansion of the Spanish economy and the beginning of the current employment crisis. From the combination of the chosen topic, the approach, and the database used, this is a novel perspective in our country. The article shows evidence of the evolution of the employment and unemployment spells, the Spanish labour market turnover degree, and the diffi culties of some groups for carrying out transition between employment and unemployment. The results obtained show a labour market in which a) transitions have come to a halt, and b) there is high job insecurity.