Packet classification by multi-level cutting of the classification space: An algorithmic-architectural solution for IP packet classification in next generation networks

Traditionally, the Internet provides only a “best-effort” service, treating all packets going to the same destination equally. However, providing differentiated services for different users based on their quality requirements is increasingly becoming a demanding issue. For this, routers need to have the capability to distinguish and isolate traffic belonging to different flows. This ability to determine the flow each packet belongs to is called packet classification. Technology vendors are reluctant to support algorithmic solutions for classification due to their non-deterministic performance. Although CAMs are favoured by technology vendors due to their deterministic high lookup rates, they suffer from the problems of high power dissipation and high silicon cost. This paper provides a new algorithmic-architectural solution for packet classification that mixes CAMs with algorithms based on multi-level cutting the classification space into smaller spaces. The provided solution utilizes the geometrical distribution of rules in the classification space. It provides the deterministic performance of CAMs, support for dynamic updates, and added flexibility for system designers.

Packet classification by multi-level cutting of the classification space

Traditionally, the Internet provides only a “best-effort” service, treating all packets going to the same destination equally. However, providing differentiated services for different users based on their quality requirements is increasingly becoming a demanding issue. For this, routers need to have the capability to distinguish and isolate traffic belonging to different flows. This ability to determine the flow each packet belongs to is called packet classification. Technology vendors are reluctant to support algorithmic solutions for classification due to their nondeterministic performance. Although content addressable memories (CAMs) are favoured by technology vendors due to their deterministic high-lookup rates, they suffer from the problems of high-power consumption and high-silicon cost. This paper provides a new algorithmic-architectural solution for packet classification that mixes CAMs with algorithms based on multilevel cutting of the classification space into smaller spaces. The provided solution utilizes the geometrical distribution of rules in the classification space. It provides the deterministic performance of CAMs, support for dynamic updates, and added flexibility for system designers.

Developing management capability within a horizontal supply chain in performance measurement deployment and evolution: A Dynamic Capabilities and Goal Theory perspective

Complex collaboration in rapidly changing business environments create challenges for management capability in Utility Horizontal Supply Chains (UHSCs) involving the deploying and evolving of performance measures. The aim of the study is twofold. First, there is a need to explore how management capability can be developed and used to deploy and evolve Performance Measurement (PM), both across a UHSC and within its constituent organisations, drawing upon a theoretical nexus of Dynamic Capability (DC) theory and complementary Goal Theory. Second, to make a contribution to knowledge by empirically building theory using these constructs to show the management motivations and behaviours within PM-based DCs. The methodology uses an interpretive theory building, multiple case based approach (n=3) as part of a USHC. The data collection methods include, interviews (n=54), focus groups (n=10), document analysis and participant observation (reflective learning logs) over a five-year period giving longitudinal data. The empirical findings lead to the development of a conceptual framework showing that management capabilities in driving PM deployment and evolution can be represented as multilevel renewal and incremental Dynamic Capabilities, which can be further understood in terms of motivation and behaviour by Goal-Theoretic constructs. In addition three interrelated cross cutting themes of management capabilities in consensus building, goal setting and resource change were identified. These management capabilities require carefully planned development and nurturing within the UHSC.