BAM Switching

SummaryBandwidth Allocation Models (BAMs) are resource allocation methods used for networks in general. BAMs are currently applied for handling resources such as bandwidth allocation in MPLS DS‐TE networks (LSP setup). In general, BAMs define resource restrictions by ‘class’ and allocate the available resources on demand. This is frequently necessary to manage large and complex systems like routing networks. G‐BAM is a new generalized BAM that, by configuration, incorporates the ‘behavior’ of existing BAMs (MAM, RDM, G‐RDM and AllocTC‐Sharing). In effect, any current available BAM ‘behavior’ is reproduced by G‐BAM by simply adjusting its configuration parameters. This paper focuses on investigating the applicability of using autonomy together with BAMs for improve performance and facilitating the management of MPLS DS‐TE networks. It is investigated the applicability of ‘BAM switching’ using a framework with autonomic characteristics. In brief, it is investigated the switching among...

The Bandwidth Allocation Models (MAM, RDM, G-RDM and AllocTC-Sharing) are management alternatives currently available which propose different resource (bandwidth) allocation strategies in multiservice networks. The BAM adoption by a network is typically a management choice and configuration task executed by the network operations and management system setup in a static or nearly static way. This paper proposes and explores the alternative of allowing BAM definition and configuration on a more dynamic way. In effect, one of the basic motivations towards BAM dynamic allocation is the fact that multiservice networks characteristics (traffic load) may change considerably in daily network operation and, as such, some dynamics in BAM allocation should be introduced in order to improve performance. A framework is presented supporting BAM dynamic allocation. The framework adopts an OpenFlow-based software-defined networking (SDN) implementation approach in order to support scalability issues with a centralized controller and management network view. The framework architecture also supports the implementation of some autonomic characteristics which, in brief, look for improving and facilitating the decision-making process involved with BAM provisioning in a multiservice network. A proof of concept is presented evaluating different BAM performance under different traffic loads in order to demonstrate the framework strategy adopted.

Bandwidth Allocation Models (BAMs) are used in order to define Bandwidth Constraints (BCs) in a per-class basis for MPLS/DS-TE networks and effectively define how network resources like bandwidth are obtained and shared by applications. The BAMs proposed (MAM – Maximum Allocation Model, RDM – Russian Dolls Model, G-RDM – Generic RDM and AllocTC-Sharing) attempt to optimize the use of bandwidth resources on a per-link basis with different allocation and resource sharing characteristics. As such, the adoption of distinct BAMs and/or changes in network resource demands (network traffic profile) may result in different network traffic allocation and operational behavior for distinct BAMs. This paper evaluates the resulting network characteristics (link utilization, preemption and flows blocking) of using BAMs dynamically with different traffic scenarios. In brief, it is investigated the dynamics of BAM switching with distinct traffic scenarios. The paper presents initially the investigated BAMs in relation to their behavior and resource allocation characteristics. Then, distinct BAMs are compared using different traffic scenarios in order to investigate the impact of a dynamic change of the BAM configured in the network. Finally, the paper shows that the adoption of a dynamic BAM allocation strategy may result in benefits for network operation in terms of link utilization, preemption and flows blocking.

—In an increasingly complex scenario for network management, a solution that allows configuration in more autonomous way with less intervention of the network manager is expected. This paper presents an evaluation of similarity functions that are necessary in the context of using a learning strategy for finding solutions. The learning approach considered is based on Case-Based Reasoning (CBR) and is applied to a network scenario where different Bandwidth Allocation Models (BAMs) behaviors are used and must be eventually switched looking for the best possible network operation. In this context, it is required to identify and configure an adequate similarity function that will be used in the learning process to recover similar solutions previously considered. This paper introduces the similarity functions, explains the relevant aspects of the learning process in which the similarity function plays a role and, finally, presents a proof of concept for a specific similarity function adopted. Results show that the similarity function was capable to get similar results from the existing use case database. As such, the use of similarity functions with CBR technique has proved to be potentially satisfactory for supporting BAM switching decisions mostly driven by the dynamics of input traffic profile.

Bandwidth Allocation Models (BAMs) were initially conceived as a support element defining rules and limits for resource allocation (bandwidth) for Traffic Classes (TCs) in IP/MPLS/DS-TE networks. BAMs evolved on its basic purpose to deploy rules and limits for TC resources focusing on IP networks. As such, distinct BAM models and solutions were developed such as MAM (Maximum Allocation Model), RDM (Russian Dolls Model), AllocTCSharing e GBAM (Generalized BAM). Another important, relevant and interesting aspect of BAM evolution is its ability to be applied on new contexts like optical networks resource allocation, cloud computing resource provisioning and support to neutrality evaluation in telephony networks. Beyond that, BAMs have been applied and researched as a basic tool and support to optimization, reconfiguration and deployment of management systems with autonomic characteristics. Considering then this large scope and research interest involved, this paper presents a tutorial vision of the BAMs focusing specifically on resource provisioning for IP/MPLS/DS-TE networks. The paper presents sequentially the concepts around BAM, starting from basic IP needs and following with MPLS, DS-TE and Traffic Engineering related aspects.  Following that, the most relevant BAMs are introduced and discussed. Finally, a simulation is presented exploring the dynamic switching of BAM models towards parameters reconfiguration and optimization like utilization, preemption and blocking among others.

Bandwidth Allocation Models (BAMs) are resource allocation methods used for networks in general. BAMs are currently applied for handling resources such as bandwidth allocation in MPLS DS-TE networks (LSP setup). In general, BAMs defines resource restrictions by “class” and allocate the available resources on demand. This is frequently necessary to manage large and complex systems like routing networks. G-BAM is a new generalized BAM that, by configuration, incorporates the “behavior” of existing BAMs (MAM, RDM, G-RDM and AllocTC-Sharing). In effect, any current available BAM “behavior” is reproduced by G-BAM by simply adjusting its configuration parameters. This paper focuses on investigating the applicability of using autonomy together with Bandwidth Allocation Models (BAMs) for improve performance and facilitating the management of MPLS DS-TE networks. It is investigated the applicability of “BAM switching” using a framework with autonomic characteristics. In brief, it is investigated the switching among “BAM behaviors” and BAM´s reconfiguration with distinct network traffic scenarios by using G-BAM. Simulation results suggest that the autonomic switching of “BAM behaviors” based on high-level management rules (SLAs, QoS or other police) may result in improving overall network management and operational parameters such as link utilization and preemption.

Bandwidth Allocation Models (BAMs) configure and handle resource allocation (bandwidth, LSPs, fibre) in networks in general (IP/MPLS/DS-TE, optical domain, other). BAMs currently available for IP/MPLS/DS-TE networks (MAM, RDM, G-RDM and AllocTC-Sharing) basically define resource restrictions (bandwidth) by “class” (traffic class, application´s class, user´s class or other grouping criteria) and allocate on demand this resource. There is a BAM allocation policy inherent for each existing model which behaves differently under distinct network state, such as heavy traffic loads and dynamic traffic and/or application scenarios. A generalized Bandwidth Allocation Model (G-BAM) is proposed in this paper. G-BAM, firstly, incorporates the inherent behavior of currently used BAMs such as MAM, RDM, G-RDM and AllocTC-Sharing in IP/MPLS/DS-TE context. G-BAM, secondly, proposes a new policy/ behavior allocation in addition to existing ones in which additional private resources are incorporated. G-BAM, thirdly, allows a smoother BAM policy transition among existing policy alternatives resulting from MAM, RDM and AllocTCSharing adoption independently. The paper focuses on the first characteristics of G-BAM which is to reproduce MAM, RDM and AllocTC-Sharing behaviors. As such, the required configuration to achieve MAM, RDM and AllocTC-Sharing behaviors is presented followed by a proof of concept. Authors argue that the G-BAM reproducibility characteristics may improve overall network resource utilization under distinct traffic profiles.