Autonomic Networking Integrated Model and Approach (ANIMA)

This chapter presents the work of the Autonomic Networking Integrated Model and Approach (ANIMA) working group of the Internet Engineering Task Force (IETF). It was formed to standardize protocols and procedures for an ANIMA autonomic network (AN) and first chartered to define the ANIMA secure autonomic network infrastructure (ANI). This chapter describes the technical history and goals leading to this working group. It then describes how the ANIMA approach provides an evolutionary approach to securing and automating networks and to provide a common infrastructure to evolve into future autonomic networks. Finally, this chapter compares this approach to adjacent standards technologies and discusses interesting next steps.

Abstract MP22: Dietary Salt Restriction And High Salt Intake Exaggerate Sympathetic Reflexes And Sensitize Central Autonomic Networks: Potential Mechanisms Of The J-shaped Curve

Observational cohort studies suggest that severe salt restriction increases cardiovascular morbidity/mortality, and the relationship between cardiovascular morbidity and dietary salt intake resembles a J-shaped curve. A high salt diet exaggerates sympathetic nerve activity (SNA) and arterial blood pressure (ABP) responses to several cardiovascular reflexes in salt-resistant animals. This study assessed whether salt restriction also exaggerates cardiovascular reflex responses and sensitizes central autonomic networks. To test this hypothesis, male Sprague-Dawley rats were fed low (0.01% NaCl), normal (0.1% NaCl), and high (4.0% NaCl) salt diet for 14-21 days. Baseline mean ABP was not different across groups (low: 104±4, normal: 107±4, high: 107±4mmHg). Activation of sciatic afferents (1ms pulse, 500uA, 5s duration, 2-20Hz) produced significantly greater increases in renal SNA (5Hz; low: 196±12, normal: 136±9, high: 177±8%, n=8, P<0.05) and ABP (5Hz; low: 29±3, normal: 16±1, high: 24±2 mmHg, n=8, P<0.05) of rats fed low and high versus normal NaCl diets. Activation of the aortic depressor nerve (2ms pulse, 500uA, 15s duration, 2-20Hz) produced significantly greater decreases in renal SNA (5Hz; low: -55±9, normal: -34±8, high: -63±13%, n=7-8, P<0.05) and ABP (5Hz; low: -31±3, normal: -15±5, high: -32±5 mmHg, n=7-8, P<0.05) of rats fed low and high versus normal NaCl diets. To test whether dietary salt intake sensitized central sympathetic circuits, microinjection of L-glutamate (0.1-1nmol, 30nL) in the rostral ventrolateral medulla produced significantly greater increases in renal SNA (0.1nmol; low: 212±15, normal: 149±8, high: 183±17%, n=7-8, P<0.05) and ABP (0.1Hz; low: 20±2, normal: 12±2, high: 22±2 mmHg, n=7-8, P<0.05) of rats fed low and high versus normal NaCl diets. Finally, rats fed low or high NaCl versus normal NaCl diets displayed exaggerated cardiovascular responses to cage switch or mild restraint and increased 24-h blood pressure variability. The present findings show that severe salt restriction and excess dietary salt intake exaggerate sympathetic and cardiovascular responses, and may be explained by a parallel change in the sensitivity of central autonomic networks to resemble a J-shaped curve.

Using the RFC 7575 and Models at Runtime for Enabling Autonomic Networking in SDN

The programmable network architectures that emerged in the last decade have allowed new ways to enable Autonomic Networks. However, there are several open issues to address before making such a possibility into a feasible reality. For instance, defining network goals, translating them into network rules, and granting the correct functioning of the network control loop in a self-adaptive manner are examples of complex tasks required to enable an autonomic networking environment. Fortunately, architectures based on the concept of Models at Runtime (MART) provide ways to overcome such complexity. This paper proposes a MART-based framework – using the RFC 7575 as reference (i.e., definitions and design goals for autonomic networking) – to implement autonomic management into a programmable network. The evaluation shows the proposed framework is suitable for satisfying the functional and performance requirements of a simulated network.

The sleeping brain switches between working memory and long-term memory processing

Both working memory (WM) and long-term memory (LTM) utilize non-rapid eye movement (NREM) sleep for improvement. LTM systems consolidation is supported by hippocampal-cortical communication, whereas WM improvement is associated with the strengthening of prefrontal-autonomic networks. Prior studies have demonstrated that these two networks demonstrate mutual antagonism during sleep; but this trade-off has not been confirmed in human sleep and its functional significance is unknown. Here, we investigated the functional impact of central and autonomic activity on LTM and WM improvement. We pharmacologically enhanced central activity and observed targeted suppression of autonomic activity, and using effective connectivity, we showed greater causal influence of central over autonomic activity. Finally, we demonstrated that the central and autonomic antagonism was reflected in a behavioral trade-off between overnight LTM and WM processing. These results suggest that NREM sleep confers benefits to working and long-term memory by switching between autonomic and central processing.

Hippocampal morphometry in sudden and unexpected death in epilepsy

ObjectiveTo determine hippocampal morphometric measures, including granule cell dispersion and features of malrotation, as potential biomarkers for sudden unexpected death in epilepsy (SUDEP) from an archival postmortem series.MethodsIn a retrospective study of 187 archival postmortems from 3 groups, SUDEP (68; 14 with hippocampal sclerosis [HS]), non-SUDEP epilepsy controls (EP-C = 66; 25 with HS), and nonepilepsy controls (NEC = 53), Nissl/hematoxylin & eosin–stained sections from left and right hippocampus from 5 coronal levels were digitized. Image analysis was carried out for granule cell layer (GCL) thickness and measurements of hippocampal dimensions (HD) for shape (width [HD1], height [HD2]) and medial hippocampal positioning in relation to the parahippocampal gyrus (PHG) length (HD3). A qualitative evaluation of hippocampal malrotational (HMAL) features, dentate gyrus invaginations (DGI), and subicular/CA1 folds (SCF) was also made.ResultsGCL thickness was increased in HS more than those without (p < 0.001). In non-HS cases, increased GCL thickness was noted in EP-C compared to NEC (p < 0.05) but not between SUDEP and NEC. There was no difference in the frequency of DGI, SCF, measurements of hippocampal shape (HD1, HD2, or ratio), or medial positioning among SUDEP, EP-C, and NEC groups, when factoring in HS, coronal level, and age at death. Comparison between left and right sides within cases showed greater PHG lengths (HD3) on the right side in the SUDEP group only (p = 0.018).ConclusionsNo hippocampal morphometric features were identified in support of either excessive granule cell dispersion or features of HMAL as definitive biomarkers for SUDEP. Asymmetries in PHG measurements in SUDEP warrant further investigation as they may indicate abnormal central autonomic networks.

Autonomic Networking Integrated Model and Approach (ANIMA)

This chapter presents the work of the Autonomic Networking Integrated Model and Approach (ANIMA) working group of the Internet Engineering Task Force (IETF). It was formed to standardize protocols and procedures for an ANIMA autonomic network (AN) and first chartered to define the ANIMA secure autonomic network infrastructure (ANI). This chapter describes the technical history and goals leading to this working group. It then describes how the ANIMA approach provides an evolutionary approach to securing and automating networks and to provide a common infrastructure to evolve into future autonomic networks. Finally, this chapter compares this approach to adjacent standards technologies and discusses interesting next steps.

Design and Evaluation of Techniques for Resilience and Survivability of the Routing Node

This paper presents the final results achieved within the EFIPSANS project on the topic of resilience and survivability in autonomic networks. In particular, the outcome of the investigation of the following issues is presented: adaptive level of recovery, unified architecture for autonomic routing resilience, synergies between autonomic fault-management and resilience in self-managing networks, as well as network resilience through autonomic reroute mechanism enhanced with multi-path node-to-node cooperation. The described ideas are supported by exhaustive descriptions and analyses featuring extensive validation results aimed to prove the applicability of the proposed concepts.